[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"_public_publisher_byId_6e7bfe59-5f4e-416b-83a0-3e0602a582c8":3,"_public_publication_all{\"sortAscending\":false,\"sortField\":\"updateTime\",\"page\":0,\"size\":10,\"facet\":true,\"searchKey\":\"publisherId:6e7bfe59-5f4e-416b-83a0-3e0602a582c8,\"}":115},{"code":4,"data":5,"meta":24},"SUCCESS",{"id":6,"createTime":7,"updateTime":8,"relativeEntities":9,"slug":10,"properties":11,"entityType":22,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":25,"subjectFields":26,"manageAffiliations":39,"indexDatabases":54,"url":90,"thumbnailPath":24,"statistic":91,"gsStatistic":24,"type":24,"analyzePriority":24},"6e7bfe59-5f4e-416b-83a0-3e0602a582c8","2023-05-29T11:43:29.032+00:00","2025-11-21T10:06:26.816+00:00",[],"ACM-Transactions-on-Intelligent-Systems-and-Technology",{"country":12,"eissn":14,"issn":16,"title":18,"introduce":20},{"VOID":13},"US",{"VOID":15},"21576904",{"VOID":17},"21576912",{"EN":19},"ACM Transactions on Intelligent Systems and Technology",{"EN":21},"ACM Transactions on Intelligent Systems and Technology is a scholarly journal that publishes the highest quality papers on intelligent systems, applicable algorithms and technology with a multi-disciplinary perspective. An intelligent system is one that uses artificial intelligence (AI) techniques to offer important services (e.g., as a component of a larger system) to allow integrated systems to perceive, reason, learn, and act intelligently in the real world. ACM TIST is published quarterly (six issues a year). Each issue has 8-11 regular papers, with around 20 published journal pages or 10,000 words per paper. Additional references, proofs, graphs or detailed experiment results can be submitted as a separate appendix, while excessively lengthy papers will be rejected automatically. Authors can include online-only appendices for additional content of their published papers and are encouraged to share their code and\u002For data with other readers.","PUBLISHER","PENDING",null,0,[27,33],{"id":28,"createTime":24,"updateTime":24,"relativeEntities":29,"label":30,"description":32,"parentId":24,"standard":24,"scholarHubFieldId":24},"6a3cb349-a9fc-40fb-9aa8-c9946de1e629",[],{"EN":31},"Artificial Intelligence",{},{"id":34,"createTime":24,"updateTime":24,"relativeEntities":35,"label":36,"description":38,"parentId":24,"standard":24,"scholarHubFieldId":24},"cfe20487-5108-4c23-a284-2aedca5fb76d",[],{"EN":37},"Theoretical Computer Science",{},[40,47],{"id":41,"createTime":24,"updateTime":24,"relativeEntities":42,"slug":24,"properties":43,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":46,"statistic":24},"3e1064b5-61a8-4ca3-bf0f-108007c66507",[],{"title":44},{"EN":45},"Association for Computing Machinery (ACM)",[],{"id":48,"createTime":24,"updateTime":24,"relativeEntities":49,"slug":24,"properties":50,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":53,"statistic":24},"e413bfb3-d7e1-44b7-91f5-e2c2169ea732",[],{"title":51},{"EN":52},"ASSOC COMPUTING MACHINERY",[],[55,72],{"id":56,"indexDatabase":57,"url":69,"indexYears":24,"academicFieldIds":70,"indexDatabaseRanking":24},"01c37a2b-a88f-40f3-8489-c75db61d75f3",{"id":58,"createTime":24,"updateTime":24,"relativeEntities":59,"label":60,"description":62,"key":65,"publicationTags":66,"standard":24},"a4921856-b128-4d9f-8f1f-e80813d3bbd4",[],{"EN":61,"VI":61},"ISI\u002FSCIE - Science Citation Index Expanded",{"EN":63,"VI":64},"SCIE database","Cơ sở dữ liệu SCIE","scie",[67,68],"SCIE","ISI","https:\u002F\u002Fmjl.clarivate.com\u002Fsearch-results?issn=2157-6904",[71],"5e7ab733-08f6-4bda-8a2e-55af36fcbd05",{"id":73,"indexDatabase":74,"url":84,"indexYears":85,"academicFieldIds":86,"indexDatabaseRanking":89},"18329d0d-fe84-4f95-9e40-09e2663bd728",{"id":75,"createTime":24,"updateTime":24,"relativeEntities":76,"label":77,"description":79,"key":81,"publicationTags":82,"standard":24},"3c7051d4-eb7d-4c57-a56b-36fc74c5d1e9",[],{"EN":78,"VI":78},"Scopus - Elsevier",{"EN":78,"VI":80},"Cơ sở dữ liệu Scopus thuộc Elsevier","scopus",[83],"SCOPUS","https:\u002F\u002Fwww.scopus.com\u002Fsourceid\u002F19700190323","2010-2025",[87,88],"8f050cfc-6be8-4218-91ba-e890405f0438","ea95f5ee-62c8-4ccb-8e3e-d3a8bc9e97cb","SCOPUS__Q1","https:\u002F\u002Ftist.acm.org\u002F",{"impactFactor":25,"impactFactorByYear":92,"i10Index":101,"i10IndexLast5Year":102,"totalPublication":103,"totalPublicationByYear":104,"totalCitation":106,"totalCitationByYear":107,"totalCitationPerPublication":112,"totalCitationPerPublicationByYear":113,"hindexLast5Year":101,"hindex":101},{"2012":93,"2013":94,"2016":95,"2017":96,"2020":97,"2021":98,"2022":99,"2023":100},1445,2151,55.5,78,4,10,38,17,5,2,6,{"2011":105,"2015":102,"2019":105,"2021":105},1,41809,{"2011":108,"2015":109,"2019":110,"2021":111},40216,1465,47,81,6968.17,{"2011":108,"2015":114,"2019":110,"2021":111},732.5,{"meta":116,"data":118},{"total":117},"8",[119,410,680,943,1552,1960,2226,2457],{"id":120,"createTime":121,"updateTime":122,"relativeEntities":123,"slug":124,"properties":125,"entityType":136,"verifyStatus":137,"verifyTime":138,"verifyNote":139,"languages":140,"translateLanguages":24,"viewCount":25,"primaryUrl":142,"fullTextUrl":24,"authors":143,"publicationType":225,"publisherRelationship":226,"citationCount":25,"citationInfo":274,"publishDate":24,"publishYear":24,"citationAnalyzeStatus":23,"lastCitationAnalyze":122,"indexDatabases":276,"openAccess":24,"references":277,"isForceReanalyzing":409},"3a51c8f0-1b46-4127-a5c2-0f54b9d35d86","2024-10-03T19:14:02.812+00:00","2026-02-01T06:26:32.645+00:00",[],"FastRx-Exploring-Fastformer-and-Memory-Augmented-Graph-Neural-Networks-for-Personalized-Medication-Recommendations",{"openalex":126,"abstract":128,"title":130,"gsPaper":132,"doi":134},{"VOID":127},"W4402576122",{"EN":129},"\u003Cjats:p>\n            Personalized medication recommendations aim to suggest a set of medications based on the clinical conditions of a patient. Not only should the patient's diagnosis, procedure, and medication history be considered, but drug-drug interactions (DDIs) must also be taken into account to prevent adverse drug reactions. Although recent studies on medication recommendation have considered DDIs and patient history, personalized disease progression and prescription have not been explicitly modeled. In this work, we proposed FastRx, a Fastformer-based medication recommendation model to capture longitudinality in patient history, in combination with Graph Convolutional Networks (GCNs) to handle DDIs and co-prescribed medications in Electronic Health Records (EHRs). Our extensive experiments on the MIMIC-III dataset demonstrated superior performance of the proposed FastRx over existing state-of-the-art models for medication recommendation. The source code and data used in the experiments are available at\n            \u003Cjats:ext-link xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" ext-link-type=\"uri\" xlink:href=\"https:\u002F\u002Fgithub.com\u002Fpnmthaoct\u002FFastRx\">https:\u002F\u002Fgithub.com\u002Fpnmthaoct\u002FFastRx\u003C\u002Fjats:ext-link>\n            .\n          \u003C\u002Fjats:p>",{"EN":131},"FastRx: Exploring Fastformer and Memory-Augmented Graph Neural Networks for Personalized Medication Recommendations",{"VOID":133},"5433272196177422515",{"VOID":135},"10.1145\u002F3696111","PUBLICATION","VERIFIED","2024-10-03T19:14:02.810+00:00","Auto Verify",[141],"EN","https:\u002F\u002Fdl.acm.org\u002Fdoi\u002F10.1145\u002F3696111",[144,163,184,203],{"id":145,"sortIndex":25,"researcher":24,"roles":146,"affiliations":147,"properties":156},"37271652-d23b-4cf6-a5e8-d979375d9cda",[],[148],{"id":149,"sortIndex":25,"affiliation":150,"properties":24},"385778ed-9775-4347-861e-0c232219a99a",{"id":149,"createTime":24,"updateTime":24,"relativeEntities":151,"slug":24,"properties":152,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":155,"statistic":24},[],{"title":153},{"EN":154},"Department of Computer Science, National Yang Ming Chiao Tung University, Taiwan and College of Information and Communication Technology, Can Tho University, Vietnam",[],{"orcid":157,"title":159,"openalex":161},{"VOID":158},"https:\u002F\u002Forcid.org\u002F0000-0001-6814-9459",{"EN":160},"Tai Tan Phan",{"VOID":162},"A5049058623",{"id":164,"sortIndex":105,"researcher":24,"roles":165,"affiliations":166,"properties":175},"69bfde8e-5fc1-4bf4-a9f3-3c8b5477e291",[],[167],{"id":168,"sortIndex":25,"affiliation":169,"properties":24},"c87fb6e5-10d9-41cf-be7f-a5666e2925cc",{"id":168,"createTime":24,"updateTime":24,"relativeEntities":170,"slug":24,"properties":171,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":174,"statistic":24},[],{"title":172},{"EN":173},"Institute of Hospital & Health Care Administration, National Yang Ming Chiao Tung University, Taiwan",[],{"orcid":176,"title":178,"gsAuthor":180,"openalex":182},{"VOID":177},"https:\u002F\u002Forcid.org\u002F0000-0002-1512-6672",{"EN":179},"Ling Chen",{"VOID":181},"WcqMzx0AAAAJ",{"VOID":183},"A5028977984",{"id":185,"sortIndex":102,"researcher":24,"roles":186,"affiliations":187,"properties":196},"3fc9f3ba-38b7-4b0b-80de-a2c30159897d",[],[188],{"id":189,"sortIndex":25,"affiliation":190,"properties":24},"745a6476-af1b-4b30-9d0a-63a13b386a25",{"id":189,"createTime":24,"updateTime":24,"relativeEntities":191,"slug":24,"properties":192,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":195,"statistic":24},[],{"title":193},{"VI":194},"School of Medicine, National Yang Ming Chiao Tung University, Taiwan",[],{"orcid":197,"title":199,"openalex":201},{"VOID":198},"https:\u002F\u002Forcid.org\u002F0009-0006-9476-2672",{"EN":200},"Chun-Hung Chen",{"VOID":202},"A5003981862",{"id":204,"sortIndex":205,"researcher":24,"roles":206,"affiliations":207,"properties":216},"6d0b5bfc-d600-4e0f-b866-90b9b162a815",3,[],[208],{"id":209,"sortIndex":25,"affiliation":210,"properties":24},"eddee1a6-3241-40bb-9f05-c55feb9e1b8c",{"id":209,"createTime":24,"updateTime":24,"relativeEntities":211,"slug":24,"properties":212,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":215,"statistic":24},[],{"title":213},{"VI":214},"Department of Computer Science, National Yang Ming Chiao Tung University, Taiwan",[],{"orcid":217,"title":219,"gsAuthor":221,"openalex":223},{"VOID":218},"https:\u002F\u002Forcid.org\u002F0000-0002-0172-7311",{"EN":220},"Wen-Chih Peng",{"VOID":222},"T5Rs-ngAAAAJ",{"VOID":224},"A5040101293","ARTICLE",{"url":24,"publisher":227,"properties":24},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":228,"slug":10,"properties":229,"entityType":22,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":25,"subjectFields":234,"manageAffiliations":243,"indexDatabases":254,"url":90,"thumbnailPath":24,"statistic":269,"gsStatistic":24,"type":24,"analyzePriority":24},[],{"country":230,"eissn":231,"issn":232,"title":233},{"VOID":13},{"VOID":15},{"VOID":17},{"EN":19},[235,239],{"id":28,"createTime":24,"updateTime":24,"relativeEntities":236,"label":237,"description":238,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":31},{},{"id":34,"createTime":24,"updateTime":24,"relativeEntities":240,"label":241,"description":242,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":37},{},[244,249],{"id":41,"createTime":24,"updateTime":24,"relativeEntities":245,"slug":24,"properties":246,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":248,"statistic":24},[],{"title":247},{"EN":45},[],{"id":48,"createTime":24,"updateTime":24,"relativeEntities":250,"slug":24,"properties":251,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":253,"statistic":24},[],{"title":252},{"EN":52},[],[255,262],{"id":56,"indexDatabase":256,"url":69,"indexYears":24,"academicFieldIds":261,"indexDatabaseRanking":24},{"id":58,"createTime":24,"updateTime":24,"relativeEntities":257,"label":258,"description":259,"key":65,"publicationTags":260,"standard":24},[],{"EN":61,"VI":61},{"EN":63,"VI":64},[67,68],[71],{"id":73,"indexDatabase":263,"url":84,"indexYears":85,"academicFieldIds":268,"indexDatabaseRanking":89},{"id":75,"createTime":24,"updateTime":24,"relativeEntities":264,"label":265,"description":266,"key":81,"publicationTags":267,"standard":24},[],{"EN":78,"VI":78},{"EN":78,"VI":80},[83],[87,88],{"impactFactor":25,"impactFactorByYear":270,"i10Index":101,"i10IndexLast5Year":102,"totalPublication":103,"totalPublicationByYear":271,"totalCitation":106,"totalCitationByYear":272,"totalCitationPerPublication":112,"totalCitationPerPublicationByYear":273,"hindexLast5Year":101,"hindex":101},{"2012":93,"2013":94,"2016":95,"2017":96,"2020":97,"2021":98,"2022":99,"2023":100},{"2011":105,"2015":102,"2019":105,"2021":105},{"2011":108,"2015":109,"2019":110,"2021":111},{"2011":108,"2015":114,"2019":110,"2021":111},{"total":25,"publishYear":24,"statisticByYear":275},{},[],[278,281,284,287,290,293,296,299,302,305,308,311,314,317,320,323,326,329,332,335,338,341,344,347,350,353,356,359,362,365,368,371,374,377,380,383,386,389,391,394,397,400,403,406],{"id":24,"text":279,"url":24,"identifiers":280},"10.1002\u002Fsim.4512",{"doi":279},{"id":24,"text":282,"url":24,"identifiers":283},"Karl Johan Åström and Tore Hägglund. 1995. PID Controllers: Theory, Design, and Tuning. ISA- The Instrumentation, Systems and Automation Society, Pennsylvania, United States. ISBN: 1-55617-516-7.",{},{"id":24,"text":285,"url":24,"identifiers":286},"10.1145\u002F3219819.3219904",{"doi":285},{"id":24,"text":288,"url":24,"identifiers":289},"Jacek M. Bajor and Thomas A. Lasko. 2017. Predicting Medications from Diagnostic Codes with Recurrent Neural Networks. In 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24-26, 2017, Conference Track Proceedings. Toulon, France, 19 pages. https:\u002F\u002Fopenreview.net\u002Fforum?id=rJEgeXFex",{},{"id":24,"text":291,"url":24,"identifiers":292},"10.1145\u002F3097983.3097997",{"doi":291},{"id":24,"text":294,"url":24,"identifiers":295},"Jie Chen, Tengfei Ma, and Cao Xiao. 2018. Fastgcn: fast learning with graph convolutional networks via importance sampling. arXiv preprint arXiv:1801.10247 (2018).",{},{"id":24,"text":297,"url":24,"identifiers":298},"10.1017\u002Fs1471068416000429",{"doi":297},{"id":24,"text":300,"url":24,"identifiers":301},"10.5555\u002F3157382.3157490",{"doi":300},{"id":24,"text":303,"url":24,"identifiers":304},"Alexey Dosovitskiy and Josip Djolonga. 2020. You Only Train Once: Loss-Conditional Training of Deep Networks. In International Conference on Learning Representations. OpenReview.net Addis Ababa Ethiopia 17 pages. https:\u002F\u002Fapi.semanticscholar.org\u002FCorpusID:214278158",{},{"id":24,"text":306,"url":24,"identifiers":307},"10.1016\u002Fs0140-6736(00)02799-9",{"doi":306},{"id":24,"text":309,"url":24,"identifiers":310},"10.1016\u002Fj.bdr.2020.100174",{"doi":309},{"id":24,"text":312,"url":24,"identifiers":313},"10.1080\u002F15374416.2015.1015133",{"doi":312},{"id":24,"text":315,"url":24,"identifiers":316},"Will Hamilton, Zhitao Ying, and Jure Leskovec. 2017. Inductive representation learning on large graphs. Advances in neural information processing systems 30 (2017), 11 pages.",{},{"id":24,"text":318,"url":24,"identifiers":319},"10.1038\u002Fsdata.2016.35",{"doi":318},{"id":24,"text":321,"url":24,"identifiers":322},"10.1001\u002Fjama.289.13.1652",{"doi":321},{"id":24,"text":324,"url":24,"identifiers":325},"Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014). http:\u002F\u002Farxiv.org\u002Fabs\u002F1412.6980",{},{"id":24,"text":327,"url":24,"identifiers":328},"Thomas N Kipf and Max Welling. 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016), 14 pages. https:\u002F\u002Fopenreview.net\u002Fforum?id=SJU4ayYgl",{},{"id":24,"text":330,"url":24,"identifiers":331},"Himabindu Lakkaraju and Cynthia Rudin. 2017. Learning cost-effective and interpretable treatment regimes. In Artificial intelligence and statistics. PMLR 166–175.",{},{"id":24,"text":333,"url":24,"identifiers":334},"10.1145\u002F3219819.3219981",{"doi":333},{"id":24,"text":336,"url":24,"identifiers":337},"10.1016\u002Fj.knosys.2023.111239",{"doi":336},{"id":24,"text":339,"url":24,"identifiers":340},"10.1093\u002Fjamia",{"doi":339},{"id":24,"text":342,"url":24,"identifiers":343},"10.1001\u002Fjama.1995.03530010049034",{"doi":342},{"id":24,"text":345,"url":24,"identifiers":346},"Chengsheng Mao, Liang Yao, and Yuan Luo. 2022. Imagegcn: Multi-relational image graph convolutional networks for disease identification with chest x-rays. IEEE transactions on medical imaging 41, 8 (2022), 1990–2003.",{},{"id":24,"text":348,"url":24,"identifiers":349},"10.1016\u002Fj.jbi.2022.104000",{"doi":348},{"id":24,"text":351,"url":24,"identifiers":352},"10.1056\u002Fnejmp1606181",{"doi":351},{"id":24,"text":354,"url":24,"identifiers":355},"10.1371\u002Fjournal.pone.0135947",{"doi":354},{"id":24,"text":357,"url":24,"identifiers":358},"10.1007\u002F978-3-642-04174-7_17",{"doi":357},{"id":24,"text":360,"url":24,"identifiers":361},"10.24963\u002Fijcai.2019",{"doi":360},{"id":24,"text":363,"url":24,"identifiers":364},"10.1609\u002Faaai.v33i01.33011126",{"doi":363},{"id":24,"text":366,"url":24,"identifiers":367},"Hongda Sun, Shufang Xie, Shuqi Li, Yuhan Chen, Ji-Rong Wen, and Rui Yan. 2022. Debiased, longitudinal and coordinated drug recommendation through multi-visit clinic records. Advances in Neural Information Processing Systems 35 (2022), 27837–27849.",{},{"id":24,"text":369,"url":24,"identifiers":370},"10.1145\u002F3534678.3539089",{"doi":369},{"id":24,"text":372,"url":24,"identifiers":373},"Nicholas P. Tatonetti, Patrick Ye, Roxana Daneshjou, and Russ B. Altman. 2012. Data-Driven Prediction of Drug Effects and Interactions. Science Translational Medicine 4 (2012), 125ra31 – 125ra31. https:\u002F\u002Fapi.semanticscholar.org\u002FCorpusID:2716426",{},{"id":24,"text":375,"url":24,"identifiers":376},"10.1145\u002F3219819.3219961",{"doi":375},{"id":24,"text":378,"url":24,"identifiers":379},"10.1145\u002F3357384.3357965",{"doi":378},{"id":24,"text":381,"url":24,"identifiers":382},"Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang, and Xing Xie. 2021. Fastformer: Additive Attention Can Be All You Need. arXiv preprint arXiv:2108.09084 (2021), 11 pages. https:\u002F\u002Farxiv.org\u002Fabs\u002F2108.09084",{},{"id":24,"text":384,"url":24,"identifiers":385},"10.1145\u002F3485447.3511936",{"doi":384},{"id":24,"text":387,"url":24,"identifiers":388},"10.1109\u002FTNNLS.2020.2978386",{"doi":387},{"id":24,"text":339,"url":24,"identifiers":390},{"doi":339},{"id":24,"text":392,"url":24,"identifiers":393},"10.24963\u002Fijcai.2021",{"doi":392},{"id":24,"text":395,"url":24,"identifiers":396},"Chaoqi Yang, Cao Xiao, Fenglong Ma, Lucas Glass, and Jimeng Sun. 2021. Safedrug: Dual molecular graph encoders for recommending effective and safe drug combinations. arXiv preprint arXiv:2105.02711 (2021). https:\u002F\u002Farxiv.org\u002Fabs\u002F2105.02711",{},{"id":24,"text":398,"url":24,"identifiers":399},"10.1145\u002F3543507.3583872",{"doi":398},{"id":24,"text":401,"url":24,"identifiers":402},"10.1609\u002Faaai.v33i01.33017370",{"doi":401},{"id":24,"text":404,"url":24,"identifiers":405},"10.1145\u002F3097983.3098109",{"doi":404},{"id":24,"text":407,"url":24,"identifiers":408},"10.1145\u002F3178876.3186116",{"doi":407},false,{"id":411,"createTime":412,"updateTime":412,"relativeEntities":413,"slug":414,"properties":415,"entityType":136,"verifyStatus":137,"verifyTime":426,"verifyNote":139,"languages":427,"translateLanguages":24,"viewCount":25,"primaryUrl":428,"fullTextUrl":24,"authors":429,"publicationType":225,"publisherRelationship":517,"citationCount":572,"citationInfo":573,"publishDate":577,"publishYear":574,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":578,"openAccess":24,"references":579,"isForceReanalyzing":409},"a42cda03-a9c0-481d-9479-1f23720d3eae","2025-02-01T05:33:42.973+00:00",[],"Traffic-Information-Publication-with-Privacy-Preservation",{"openalex":416,"mag":418,"abstract":420,"title":422,"doi":424},{"VOID":417},"W2039049533",{"VOID":419},"2039049533",{"EN":421},"\u003Cjats:p>\n            We are experiencing the expanding use of location-based services such as AT&T’s TeleNav GPS Navigator and Intel’s Thing Finder. Existing location-based services have collected a large amount of location data, which has great potential for statistical usage in applications like traffic flow analysis, infrastructure planning, and advertisement dissemination. The key challenge is how to wisely use the data without violating each user’s location privacy concerns. In this article, we first identify a new privacy problem, namely, the\n            \u003Cjats:italic>inference-route\u003C\u002Fjats:italic>\n            problem, and then present our anonymization algorithms for privacy-preserving trajectory publishing. The experimental results have demonstrated that our approach outperforms the latest related work in terms of both efficiency and effectiveness.\n          \u003C\u002Fjats:p>",{"EN":423},"Traffic Information Publication with Privacy Preservation",{"VOID":425},"10.1145\u002F2542666","2025-02-01T05:33:42.972+00:00",[141],"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002F10.1145\u002F2542666",[430,447,464,481,498],{"id":431,"sortIndex":25,"researcher":24,"roles":432,"affiliations":433,"properties":442},"a7ba8ba0-8fb4-478c-8130-b36c915213d9",[],[434],{"id":435,"sortIndex":25,"affiliation":436,"properties":24},"af075999-e0d3-4d3b-8de0-a224f361c2d2",{"id":435,"createTime":24,"updateTime":24,"relativeEntities":437,"slug":24,"properties":438,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":441,"statistic":24},[],{"title":439},{"VI":440},"Missouri University\r\nof Science & Technology",[],{"title":443,"openalex":445},{"EN":444},"Sashi Gurung",{"VOID":446},"A5108240414",{"id":448,"sortIndex":105,"researcher":24,"roles":449,"affiliations":450,"properties":457},"20bb267c-fd8b-43a5-bdac-6db7c3ee45d9",[],[451],{"id":435,"sortIndex":25,"affiliation":452,"properties":24},{"id":435,"createTime":24,"updateTime":24,"relativeEntities":453,"slug":24,"properties":454,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":456,"statistic":24},[],{"title":455},{"VI":440},[],{"orcid":458,"title":460,"openalex":462},{"VOID":459},"https:\u002F\u002Forcid.org\u002F0000-0002-3062-8240",{"EN":461},"Dan Lin",{"VOID":463},"A5101655052",{"id":465,"sortIndex":102,"researcher":24,"roles":466,"affiliations":467,"properties":474},"3bf3a24b-68c5-49b7-8a33-bb03460cd7cc",[],[468],{"id":435,"sortIndex":25,"affiliation":469,"properties":24},{"id":435,"createTime":24,"updateTime":24,"relativeEntities":470,"slug":24,"properties":471,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":473,"statistic":24},[],{"title":472},{"VI":440},[],{"orcid":475,"title":477,"openalex":479},{"VOID":476},"https:\u002F\u002Forcid.org\u002F0000-0002-9240-5851",{"EN":478},"Wei Jiang",{"VOID":480},"A5002942261",{"id":482,"sortIndex":205,"researcher":24,"roles":483,"affiliations":484,"properties":491},"2523f565-ba09-412e-9315-534cafd3ec9a",[],[485],{"id":435,"sortIndex":25,"affiliation":486,"properties":24},{"id":435,"createTime":24,"updateTime":24,"relativeEntities":487,"slug":24,"properties":488,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":490,"statistic":24},[],{"title":489},{"VI":440},[],{"orcid":492,"title":494,"openalex":496},{"VOID":493},"https:\u002F\u002Forcid.org\u002F0000-0002-9510-0762",{"EN":495},"Ali R. Hurson",{"VOID":497},"A5084254004",{"id":499,"sortIndex":97,"researcher":24,"roles":500,"affiliations":501,"properties":510},"231b873c-4bc8-4c15-af5e-10e696057159",[],[502],{"id":503,"sortIndex":25,"affiliation":504,"properties":24},"16571312-b361-4675-b1ce-c0cf9d2cf37c",{"id":503,"createTime":24,"updateTime":24,"relativeEntities":505,"slug":24,"properties":506,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":509,"statistic":24},[],{"title":507},{"VI":508},"University of Melbourne, Australia",[],{"orcid":511,"title":513,"openalex":515},{"VOID":512},"https:\u002F\u002Forcid.org\u002F0000-0002-8132-6250",{"EN":514},"Rui Zhang",{"VOID":516},"A5100422092",{"url":24,"publisher":518,"properties":565},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":519,"slug":10,"properties":520,"entityType":22,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":25,"subjectFields":525,"manageAffiliations":534,"indexDatabases":545,"url":90,"thumbnailPath":24,"statistic":560,"gsStatistic":24,"type":24,"analyzePriority":24},[],{"country":521,"eissn":522,"issn":523,"title":524},{"VOID":13},{"VOID":15},{"VOID":17},{"EN":19},[526,530],{"id":28,"createTime":24,"updateTime":24,"relativeEntities":527,"label":528,"description":529,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":31},{},{"id":34,"createTime":24,"updateTime":24,"relativeEntities":531,"label":532,"description":533,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":37},{},[535,540],{"id":41,"createTime":24,"updateTime":24,"relativeEntities":536,"slug":24,"properties":537,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":539,"statistic":24},[],{"title":538},{"EN":45},[],{"id":48,"createTime":24,"updateTime":24,"relativeEntities":541,"slug":24,"properties":542,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":544,"statistic":24},[],{"title":543},{"EN":52},[],[546,553],{"id":56,"indexDatabase":547,"url":69,"indexYears":24,"academicFieldIds":552,"indexDatabaseRanking":24},{"id":58,"createTime":24,"updateTime":24,"relativeEntities":548,"label":549,"description":550,"key":65,"publicationTags":551,"standard":24},[],{"EN":61,"VI":61},{"EN":63,"VI":64},[67,68],[71],{"id":73,"indexDatabase":554,"url":84,"indexYears":85,"academicFieldIds":559,"indexDatabaseRanking":89},{"id":75,"createTime":24,"updateTime":24,"relativeEntities":555,"label":556,"description":557,"key":81,"publicationTags":558,"standard":24},[],{"EN":78,"VI":78},{"EN":78,"VI":80},[83],[87,88],{"impactFactor":25,"impactFactorByYear":561,"i10Index":101,"i10IndexLast5Year":102,"totalPublication":103,"totalPublicationByYear":562,"totalCitation":106,"totalCitationByYear":563,"totalCitationPerPublication":112,"totalCitationPerPublicationByYear":564,"hindexLast5Year":101,"hindex":101},{"2012":93,"2013":94,"2016":95,"2017":96,"2020":97,"2021":98,"2022":99,"2023":100},{"2011":105,"2015":102,"2019":105,"2021":105},{"2011":108,"2015":109,"2019":110,"2021":111},{"2011":108,"2015":114,"2019":110,"2021":111},{"issue":566,"pages":568,"volume":570},{"VOID":567},"3",{"VOID":569},"1-26",{"VOID":571},"5",39,{"total":572,"publishYear":574,"statisticByYear":575},2014,{"2014":105,"2016":102,"2017":105,"2018":97,"2019":97,"2020":103,"2021":97,"2022":103,"2023":576,"2024":205},8,"2014-10-01",[67,89],[580,583,586,589,592,595,598,601,604,607,610,613,616,619,622,626,629,632,635,638,641,644,647,650,653,656,659,662,665,668,671,674,677],{"id":24,"text":581,"url":24,"identifiers":582},"10.1109\u002FICDMW.2007.52",{"doi":581},{"id":24,"text":584,"url":24,"identifiers":585},"10.1109\u002FTKDE.2009.213",{"doi":584},{"id":24,"text":587,"url":24,"identifiers":588},"10.1109\u002FICDE.2008.4497446",{"doi":587},{"id":24,"text":590,"url":24,"identifiers":591},"10.1016\u002Fj.is.2010.05.003",{"doi":590},{"id":24,"text":593,"url":24,"identifiers":594},"10.1145\u002F342009.335438",{"doi":593},{"id":24,"text":596,"url":24,"identifiers":597},"10.1145\u002F1667502.1667510",{"doi":596},{"id":24,"text":599,"url":24,"identifiers":600},"10.1007\u002Fs00778-006-0034-x",{"doi":599},{"id":24,"text":602,"url":24,"identifiers":603},"10.1007\u002F11552338_13",{"doi":602},{"id":24,"text":605,"url":24,"identifiers":606},"T. Brinkhoff. 2004. A Framework for Generating Network-Based Moving Objects. Available at http:\u002F\u002Fwww.fh-oow.de\u002Finstitute\u002Fiapg\u002Fpersonen\u002Fbrinkhoff\u002Fgenerator.  T. Brinkhoff. 2004. A Framework for Generating Network-Based Moving Objects. Available at http:\u002F\u002Fwww.fh-oow.de\u002Finstitute\u002Fiapg\u002Fpersonen\u002Fbrinkhoff\u002Fgenerator.",{},{"id":24,"text":608,"url":24,"identifiers":609},"R. Chen B. Fung and B. Desai. 2011. Differentially private trajectory data publication. arXiv preprint arXiv:1112.2020 (2011).  R. Chen B. Fung and B. Desai. 2011. Differentially private trajectory data publication. arXiv preprint arXiv:1112.2020 (2011).",{},{"id":24,"text":611,"url":24,"identifiers":612},"10.1016\u002Fj.ins.2012.04.015",{"doi":611},{"id":24,"text":614,"url":24,"identifiers":615},"10.1109\u002FMDM.2007.18",{"doi":614},{"id":24,"text":617,"url":24,"identifiers":618},"10.1109\u002FSECURECOMM.2005.33",{"doi":617},{"id":24,"text":620,"url":24,"identifiers":621},"10.1145\u002F1315245.1315266",{"doi":620},{"id":24,"text":623,"url":24,"identifiers":624},"Z. Huo X. Meng and R. Zhang. 2013. Feel free to check-in: Privacy alert against hidden location inference attacks in GeoSNs. In Database Systems for Advanced Applications. 377--391.  Z. Huo X. Meng and R. Zhang. 2013. Feel free to check-in: Privacy alert against hidden location inference attacks in GeoSNs. In Database Systems for Advanced Applications. 377--391.",{"doi":625},"10.1007\u002F978-3-642-37487-6_29",{"id":24,"text":627,"url":24,"identifiers":628},"10.1007\u002F978-3-642-12098-5_2",{"doi":627},{"id":24,"text":630,"url":24,"identifiers":631},"10.1145\u002F1645953.1646140",{"doi":630},{"id":24,"text":633,"url":24,"identifiers":634},"10.1109\u002FMDM.2007.45",{"doi":633},{"id":24,"text":636,"url":24,"identifiers":637},"10.5555\u002F1824401.1824403",{"doi":636},{"id":24,"text":639,"url":24,"identifiers":640},"10.5555\u002F2019316.2019319",{"doi":639},{"id":24,"text":642,"url":24,"identifiers":643},"10.5555\u002F1556406.1556410",{"doi":642},{"id":24,"text":645,"url":24,"identifiers":646},"10.1109\u002FTKDE.2004.77",{"doi":645},{"id":24,"text":648,"url":24,"identifiers":649},"Pensa R. G., Proc. of the International Workshop on Privacy in Location-Based Applications.",{},{"id":24,"text":651,"url":24,"identifiers":652},"10.1142\u002FS021848850200165X",{"doi":651},{"id":24,"text":654,"url":24,"identifiers":655},"J. C. Tanner. 2008. In search of LBS accountability. In Telecom Asia.  J. C. Tanner. 2008. In search of LBS accountability. In Telecom Asia.",{},{"id":24,"text":657,"url":24,"identifiers":658},"10.1109\u002FMDM.2008.29",{"doi":657},{"id":24,"text":660,"url":24,"identifiers":661},"10.1145\u002F321796.321811",{"doi":660},{"id":24,"text":663,"url":24,"identifiers":664},"10.1145\u002F2339530.2339562",{"doi":663},{"id":24,"text":666,"url":24,"identifiers":667},"10.1109\u002FICDE.2013.6544830",{"doi":666},{"id":24,"text":669,"url":24,"identifiers":670},"10.14778\u002F2536274.2536275",{"doi":669},{"id":24,"text":672,"url":24,"identifiers":673},"10.1145\u002F1516360.1516370",{"doi":672},{"id":24,"text":675,"url":24,"identifiers":676},"10.1023\u002FA:1007652502315",{"doi":675},{"id":24,"text":678,"url":24,"identifiers":679},"10.1007\u002Fs10115-008-0179-6",{"doi":678},{"id":681,"createTime":682,"updateTime":682,"relativeEntities":683,"slug":684,"properties":685,"entityType":136,"verifyStatus":137,"verifyTime":682,"verifyNote":139,"languages":696,"translateLanguages":24,"viewCount":25,"primaryUrl":697,"fullTextUrl":24,"authors":698,"publicationType":225,"publisherRelationship":752,"citationCount":805,"citationInfo":806,"publishDate":817,"publishYear":807,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":818,"openAccess":24,"references":819,"isForceReanalyzing":409},"55cf8dbe-17ce-47f8-ad64-4b6c68225d4a","2025-01-27T11:51:23.717+00:00",[],"Mining-Travel-Patterns-from-Geotagged-Photos",{"openalex":686,"mag":688,"abstract":690,"title":692,"doi":694},{"VOID":687},"W2068160960",{"VOID":689},"2068160960",{"EN":691},"\u003Cjats:p>Recently, the phenomenal advent of photo-sharing services, such as Flickr and Panoramio, have led to volumous community-contributed photos with text tags, timestamps, and geographic references on the Internet. The photos, together with their time- and geo-references, become the digital footprints of photo takers and implicitly document their spatiotemporal movements. This study aims to leverage the wealth of these enriched online photos to analyze people’s travel patterns at the local level of a tour destination. Specifically, we focus our analysis on two aspects: (1) tourist movement patterns in relation to the regions of attractions (RoA), and (2) topological characteristics of travel routes by different tourists. To do so, we first build a statistically reliable database of travel paths from a noisy pool of community-contributed geotagged photos on the Internet. We then investigate the tourist traffic flow among different RoAs by exploiting the Markov chain model. Finally, the topological characteristics of travel routes are analyzed by performing a sequence clustering on tour routes. Testings on four major cities demonstrate promising results of the proposed system.\u003C\u002Fjats:p>",{"EN":693},"Mining Travel Patterns from Geotagged Photos",{"VOID":695},"10.1145\u002F2168752.2168770",[141],"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002F10.1145\u002F2168752.2168770",[699,716,735],{"id":700,"sortIndex":25,"researcher":24,"roles":701,"affiliations":702,"properties":711},"d2028431-46ca-4ba2-9e90-97b0e89be8d5",[],[703],{"id":704,"sortIndex":25,"affiliation":705,"properties":24},"0d3a4f3b-9de1-42d8-80f5-4efc1d8b443e",{"id":704,"createTime":24,"updateTime":24,"relativeEntities":706,"slug":24,"properties":707,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":710,"statistic":24},[],{"title":708},{"VI":709},"Institute for Infocomm Research, Singapore",[],{"title":712,"openalex":714},{"EN":713},"Yan-Tao Zheng",{"VOID":715},"A5111540763",{"id":717,"sortIndex":105,"researcher":24,"roles":718,"affiliations":719,"properties":728},"5eb8ceed-1e84-4b29-b73e-405986dbd8c2",[],[720],{"id":721,"sortIndex":25,"affiliation":722,"properties":24},"63e4ec69-5109-4d83-87ea-02cefba68e2e",{"id":721,"createTime":24,"updateTime":24,"relativeEntities":723,"slug":24,"properties":724,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":727,"statistic":24},[],{"title":725},{"EN":726},"National University of Singapore;",[],{"orcid":729,"title":731,"openalex":733},{"VOID":730},"https:\u002F\u002Forcid.org\u002F0000-0003-2510-8993",{"EN":732},"Zheng-Jun Zha",{"VOID":734},"A5003217535",{"id":736,"sortIndex":102,"researcher":24,"roles":737,"affiliations":738,"properties":745},"da6f0f47-164c-4303-9831-5bfa482f1933",[],[739],{"id":721,"sortIndex":25,"affiliation":740,"properties":24},{"id":721,"createTime":24,"updateTime":24,"relativeEntities":741,"slug":24,"properties":742,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":744,"statistic":24},[],{"title":743},{"EN":726},[],{"orcid":746,"title":748,"openalex":750},{"VOID":747},"https:\u002F\u002Forcid.org\u002F0000-0001-6097-7807",{"EN":749},"Tat‐Seng Chua",{"VOID":751},"A5089404640",{"url":24,"publisher":753,"properties":800},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":754,"slug":10,"properties":755,"entityType":22,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":25,"subjectFields":760,"manageAffiliations":769,"indexDatabases":780,"url":90,"thumbnailPath":24,"statistic":795,"gsStatistic":24,"type":24,"analyzePriority":24},[],{"country":756,"eissn":757,"issn":758,"title":759},{"VOID":13},{"VOID":15},{"VOID":17},{"EN":19},[761,765],{"id":28,"createTime":24,"updateTime":24,"relativeEntities":762,"label":763,"description":764,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":31},{},{"id":34,"createTime":24,"updateTime":24,"relativeEntities":766,"label":767,"description":768,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":37},{},[770,775],{"id":41,"createTime":24,"updateTime":24,"relativeEntities":771,"slug":24,"properties":772,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":774,"statistic":24},[],{"title":773},{"EN":45},[],{"id":48,"createTime":24,"updateTime":24,"relativeEntities":776,"slug":24,"properties":777,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":779,"statistic":24},[],{"title":778},{"EN":52},[],[781,788],{"id":56,"indexDatabase":782,"url":69,"indexYears":24,"academicFieldIds":787,"indexDatabaseRanking":24},{"id":58,"createTime":24,"updateTime":24,"relativeEntities":783,"label":784,"description":785,"key":65,"publicationTags":786,"standard":24},[],{"EN":61,"VI":61},{"EN":63,"VI":64},[67,68],[71],{"id":73,"indexDatabase":789,"url":84,"indexYears":85,"academicFieldIds":794,"indexDatabaseRanking":89},{"id":75,"createTime":24,"updateTime":24,"relativeEntities":790,"label":791,"description":792,"key":81,"publicationTags":793,"standard":24},[],{"EN":78,"VI":78},{"EN":78,"VI":80},[83],[87,88],{"impactFactor":25,"impactFactorByYear":796,"i10Index":101,"i10IndexLast5Year":102,"totalPublication":103,"totalPublicationByYear":797,"totalCitation":106,"totalCitationByYear":798,"totalCitationPerPublication":112,"totalCitationPerPublicationByYear":799,"hindexLast5Year":101,"hindex":101},{"2012":93,"2013":94,"2016":95,"2017":96,"2020":97,"2021":98,"2022":99,"2023":100},{"2011":105,"2015":102,"2019":105,"2021":105},{"2011":108,"2015":109,"2019":110,"2021":111},{"2011":108,"2015":114,"2019":110,"2021":111},{"issue":801,"pages":802,"volume":804},{"VOID":567},{"VOID":803},"1-18",{"VOID":567},224,{"total":805,"publishYear":807,"statisticByYear":808},2012,{"2012":205,"2013":809,"2014":810,"2015":100,"2016":811,"2017":812,"2018":813,"2019":810,"2020":814,"2021":815,"2022":816,"2023":97,"2024":97},14,23,29,27,22,24,20,11,"2012-05-01",[67,89],[820,823,826,829,832,835,837,840,843,846,849,852,855,858,861,864,867,870,873,876,879,882,885,888,891,894,898,901,904,907,910,913,916,919,922,925,928,931,934,937,940],{"id":24,"text":821,"url":24,"identifiers":822},"10.1016\u002Fj.tra.2006.07.003",{"doi":821},{"id":24,"text":824,"url":24,"identifiers":825},"Bishop C. M., Pattern Recognition and Machine Learning",{},{"id":24,"text":827,"url":24,"identifiers":828},"10.1145\u002F1526709.1526812",{"doi":827},{"id":24,"text":830,"url":24,"identifiers":831},"Das G., Proceedings of the 1st European Symposium on Principles of Data Mining and Knowledge Discovery. Springer-Verlag",{},{"id":24,"text":833,"url":24,"identifiers":834},"10.1145\u002F1810617.1810626",{"doi":833},{"id":24,"text":833,"url":24,"identifiers":836},{"doi":833},{"id":24,"text":838,"url":24,"identifiers":839},"10.1145\u002F1772690.1772815",{"doi":838},{"id":24,"text":841,"url":24,"identifiers":842},"Degroot M. H. and Schervish M. J. 2001. Probability and Statistics 3rd Ed. Addison Wesley. Degroot M. H. and Schervish M. J. 2001. Probability and Statistics 3rd Ed. Addison Wesley.",{},{"id":24,"text":844,"url":24,"identifiers":845},"10.1090\u002FS0273-0979-08-01238-X",{"doi":844},{"id":24,"text":847,"url":24,"identifiers":848},"10.1007\u002F11863939_5",{"doi":847},{"id":24,"text":850,"url":24,"identifiers":851},"Ester M., Proceedings of the Conference on Knowledge Discovery and Data Mining. ACM",{},{"id":24,"text":853,"url":24,"identifiers":854},"10.1145\u002F1281192.1281230",{"doi":853},{"id":24,"text":856,"url":24,"identifiers":857},"Girardin F., B. J., 2008, Proceedings of 1st International Workshop on Trends in Pervasive and Ubiquitous Geotechnology and Geoinformation. ACM",{},{"id":24,"text":859,"url":24,"identifiers":860},"Ishikawa Y., Proceedings of the 2nd International Workshop on Spatio-Temporal Database Management (STDBM’04)",{},{"id":24,"text":862,"url":24,"identifiers":863},"Kalogerakis E., Proceedings of the International Conference on Computer Vision.",{},{"id":24,"text":865,"url":24,"identifiers":866},"Kawai Y., Proceedings of the IEEE International Conference on Multimedia and Expo. 990--993",{},{"id":24,"text":868,"url":24,"identifiers":869},"10.1145\u002F1291233.1291384",{"doi":868},{"id":24,"text":871,"url":24,"identifiers":872},"10.1177\u002F001316447003000308",{"doi":871},{"id":24,"text":874,"url":24,"identifiers":875},"10.1145\u002F1871437.1871513",{"doi":874},{"id":24,"text":877,"url":24,"identifiers":878},"10.1057\u002Fpalgrave.thr.6050027",{"doi":877},{"id":24,"text":880,"url":24,"identifiers":881},"10.1016\u002FS0261-5177(02)00026-2",{"doi":880},{"id":24,"text":883,"url":24,"identifiers":884},"10.1016\u002Fj.annals.2005.12.002",{"doi":883},{"id":24,"text":886,"url":24,"identifiers":887},"10.1007\u002F978-3-540-88682-2_33",{"doi":886},{"id":24,"text":889,"url":24,"identifiers":890},"Li Y., Proceedings of the International Conference on Computer Vision. 1957--1964",{},{"id":24,"text":892,"url":24,"identifiers":893},"10.1145\u002F1873951.1873972",{"doi":892},{"id":24,"text":895,"url":24,"identifiers":896},"McKercher B. and Lew A. 2004. Tourist flows and the spatial distribution of tourists. In A Companion to Tourism Chapter 3 Wiley Online Library. McKercher B. and Lew A. 2004. Tourist flows and the spatial distribution of tourists. In A Companion to Tourism Chapter 3 Wiley Online Library.",{"doi":897},"10.1002\u002F9780470752272.ch3",{"id":24,"text":899,"url":24,"identifiers":900},"10.1080\u002F14616680802236352",{"doi":899},{"id":24,"text":902,"url":24,"identifiers":903},"10.1109\u002FTKDE.2003.1161583",{"doi":902},{"id":24,"text":905,"url":24,"identifiers":906},"10.1145\u002F1277741.1277762",{"doi":905},{"id":24,"text":908,"url":24,"identifiers":909},"Upton G. J. G. and Fingleton B. 1989. Spatial Data Analysis by Example Vol. 2 Categorical and Directional Data. Wiley & Sons. Upton G. J. G. and Fingleton B. 1989. Spatial Data Analysis by Example Vol. 2 Categorical and Directional Data. Wiley & Sons.",{},{"id":24,"text":911,"url":24,"identifiers":912},"10.1007\u002Fs10618-007-0079-5",{"doi":911},{"id":24,"text":914,"url":24,"identifiers":915},"10.1145\u002F956750.956777",{"doi":914},{"id":24,"text":917,"url":24,"identifiers":918},"10.1016\u002Fj.matcom.2008.06.007",{"doi":917},{"id":24,"text":920,"url":24,"identifiers":921},"10.1145\u002F1646396.1646414",{"doi":920},{"id":24,"text":923,"url":24,"identifiers":924},"10.1145\u002F1823746.1823747",{"doi":923},{"id":24,"text":926,"url":24,"identifiers":927},"10.1109\u002FISUC.2008.19",{"doi":926},{"id":24,"text":929,"url":24,"identifiers":930},"10.1145\u002F1889681.1889683",{"doi":929},{"id":24,"text":932,"url":24,"identifiers":933},"10.1145\u002F1526709.1526816",{"doi":932},{"id":24,"text":935,"url":24,"identifiers":936},"Zheng Y.-T., Proceedings of the 17th International Conference on Advances in Multimedia Modeling Part (MMM’11)",{},{"id":24,"text":938,"url":24,"identifiers":939},"Zheng Y.-T., Proceedings of the International Conference on Computer Vision and Pattern Recognition.",{},{"id":24,"text":941,"url":24,"identifiers":942},"10.1145\u002F1631272.1631468",{"doi":941},{"id":944,"createTime":945,"updateTime":946,"relativeEntities":947,"slug":948,"properties":949,"entityType":136,"verifyStatus":137,"verifyTime":964,"verifyNote":139,"languages":965,"translateLanguages":966,"viewCount":25,"primaryUrl":968,"fullTextUrl":24,"authors":969,"publicationType":225,"publisherRelationship":989,"citationCount":1043,"citationInfo":1044,"publishDate":1056,"publishYear":1045,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":1057,"openAccess":24,"references":1058,"isForceReanalyzing":409},"2412c08a-7aad-464a-90a7-72ec8e3c4808","2024-09-17T09:34:44.326+00:00","2024-12-29T01:11:29.199+00:00",[],"Trajectory-Data-Mining",{"openalex":950,"mag":952,"abstract":954,"title":957,"keywords":960,"doi":962},{"VOID":951},"W2126194848",{"VOID":953},"2126194848",{"EN":955,"VI":956},"\u003Cjats:p>\n            The advances in location-acquisition and mobile computing techniques have generated massive spatial trajectory data, which represent the mobility of a diversity of moving objects, such as people, vehicles, and animals. Many techniques have been proposed for processing, managing, and mining trajectory data in the past decade, fostering a broad range of applications. In this article, we conduct a systematic survey on the major research into\n            \u003Cjats:italic>trajectory data mining\u003C\u002Fjats:italic>\n            , providing a panorama of the field as well as the scope of its research topics. Following a road map from the derivation of trajectory data, to trajectory data preprocessing, to trajectory data management, and to a variety of mining tasks (such as trajectory pattern mining, outlier detection, and trajectory classification), the survey explores the connections, correlations, and differences among these existing techniques. This survey also introduces the methods that transform trajectories into other data formats, such as graphs, matrices, and tensors, to which more data mining and machine learning techniques can be applied. Finally, some public trajectory datasets are presented. This survey can help shape the field of\n            \u003Cjats:italic>trajectory data mining\u003C\u002Fjats:italic>\n            , providing a quick understanding of this field to the community.\n          \u003C\u002Fjats:p>","\u003Cjats:p>\n            Những tiến bộ trong việc thu thập vị trí và kỹ thuật tính toán di động đã tạo ra một lượng lớn dữ liệu quỹ đạo không gian, đại diện cho sự di chuyển của đa dạng các đối tượng di chuyển, chẳng hạn như con người, phương tiện và động vật. Nhiều kỹ thuật đã được đề xuất để xử lý, quản lý và khai thác dữ liệu quỹ đạo trong thập kỷ qua, thúc đẩy một loạt ứng dụng rộng rãi. Trong bài báo này, chúng tôi tiến hành một khảo sát có hệ thống về các nghiên cứu chính trong lĩnh vực\n            \u003Cjats:italic>khai thác dữ liệu quỹ đạo\u003C\u002Fjats:italic>\n            , cung cấp một cái nhìn tổng quát về lĩnh vực cũng như phạm vi các chủ đề nghiên cứu của nó. Với một lộ trình từ việc thu thập dữ liệu quỹ đạo, đến tiền xử lý dữ liệu quỹ đạo, đến quản lý dữ liệu quỹ đạo, và đến nhiều nhiệm vụ khai thác khác nhau (chẳng hạn như khai thác mẫu quỹ đạo, phát hiện ngoại lệ, và phân loại quỹ đạo), khảo sát khám phá các mối liên hệ, tương quan, và sự khác biệt giữa các kỹ thuật hiện có. Khảo sát này cũng giới thiệu các phương pháp chuyển đổi quỹ đạo thành các định dạng dữ liệu khác, chẳng hạn như đồ thị, ma trận, và tensor, mà các kỹ thuật khai thác dữ liệu và học máy khác có thể được áp dụng. Cuối cùng, một số tập dữ liệu quỹ đạo công khai được trình bày. Khảo sát này có thể giúp định hình lĩnh vực\n            \u003Cjats:italic>khai thác dữ liệu quỹ đạo\u003C\u002Fjats:italic>\n            , cung cấp sự hiểu biết nhanh chóng về lĩnh vực này cho cộng đồng.\n          \u003C\u002Fjats:p>",{"EN":958,"VI":959},"Trajectory Data Mining","Khai thác Dữ liệu Đường đi",{"VI":961},"",{"VOID":963},"10.1145\u002F2743025","2024-09-17T09:34:44.325+00:00",[141],[967],"VI","https:\u002F\u002Fdl.acm.org\u002Fdoi\u002F10.1145\u002F2743025",[970],{"id":971,"sortIndex":25,"researcher":24,"roles":972,"affiliations":973,"properties":982},"a296a5af-0ccf-427f-9171-70894dc71896",[],[974],{"id":975,"sortIndex":25,"affiliation":976,"properties":24},"482e7f24-8a28-4c2f-80de-158eebdd82ff",{"id":975,"createTime":24,"updateTime":24,"relativeEntities":977,"slug":24,"properties":978,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":981,"statistic":24},[],{"title":979},{"VI":980},"Microsoft Research, Beijing, China",[],{"orcid":983,"title":985,"openalex":987},{"VOID":984},"https:\u002F\u002Forcid.org\u002F0000-0002-5224-4344",{"EN":986},"Yu Zheng",{"VOID":988},"A5100681023",{"url":24,"publisher":990,"properties":1037},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":991,"slug":10,"properties":992,"entityType":22,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":25,"subjectFields":997,"manageAffiliations":1006,"indexDatabases":1017,"url":90,"thumbnailPath":24,"statistic":1032,"gsStatistic":24,"type":24,"analyzePriority":24},[],{"country":993,"eissn":994,"issn":995,"title":996},{"VOID":13},{"VOID":15},{"VOID":17},{"EN":19},[998,1002],{"id":28,"createTime":24,"updateTime":24,"relativeEntities":999,"label":1000,"description":1001,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":31},{},{"id":34,"createTime":24,"updateTime":24,"relativeEntities":1003,"label":1004,"description":1005,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":37},{},[1007,1012],{"id":41,"createTime":24,"updateTime":24,"relativeEntities":1008,"slug":24,"properties":1009,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1011,"statistic":24},[],{"title":1010},{"EN":45},[],{"id":48,"createTime":24,"updateTime":24,"relativeEntities":1013,"slug":24,"properties":1014,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1016,"statistic":24},[],{"title":1015},{"EN":52},[],[1018,1025],{"id":56,"indexDatabase":1019,"url":69,"indexYears":24,"academicFieldIds":1024,"indexDatabaseRanking":24},{"id":58,"createTime":24,"updateTime":24,"relativeEntities":1020,"label":1021,"description":1022,"key":65,"publicationTags":1023,"standard":24},[],{"EN":61,"VI":61},{"EN":63,"VI":64},[67,68],[71],{"id":73,"indexDatabase":1026,"url":84,"indexYears":85,"academicFieldIds":1031,"indexDatabaseRanking":89},{"id":75,"createTime":24,"updateTime":24,"relativeEntities":1027,"label":1028,"description":1029,"key":81,"publicationTags":1030,"standard":24},[],{"EN":78,"VI":78},{"EN":78,"VI":80},[83],[87,88],{"impactFactor":25,"impactFactorByYear":1033,"i10Index":101,"i10IndexLast5Year":102,"totalPublication":103,"totalPublicationByYear":1034,"totalCitation":106,"totalCitationByYear":1035,"totalCitationPerPublication":112,"totalCitationPerPublicationByYear":1036,"hindexLast5Year":101,"hindex":101},{"2012":93,"2013":94,"2016":95,"2017":96,"2020":97,"2021":98,"2022":99,"2023":100},{"2011":105,"2015":102,"2019":105,"2021":105},{"2011":108,"2015":109,"2019":110,"2021":111},{"2011":108,"2015":114,"2019":110,"2021":111},{"issue":1038,"pages":1039,"volume":1041},{"VOID":567},{"VOID":1040},"1-41",{"VOID":1042},"6",1375,{"total":1043,"publishYear":1045,"statisticByYear":1046},2015,{"2015":100,"2016":1047,"2017":1048,"2018":1049,"2019":1050,"2020":1051,"2021":1052,"2022":1053,"2023":1054,"2024":1055},95,147,188,206,204,183,146,123,63,"2015-05-20",[67,89],[1059,1061,1064,1068,1071,1074,1077,1080,1083,1086,1089,1092,1095,1098,1101,1104,1107,1110,1113,1116,1119,1122,1125,1128,1131,1135,1138,1142,1145,1148,1151,1154,1157,1160,1162,1164,1167,1170,1173,1176,1179,1182,1185,1189,1192,1195,1198,1202,1205,1208,1211,1214,1217,1221,1224,1227,1230,1233,1236,1239,1242,1245,1248,1251,1254,1257,1260,1263,1266,1269,1272,1275,1277,1280,1283,1286,1289,1292,1295,1298,1301,1304,1307,1310,1313,1316,1319,1322,1325,1328,1331,1334,1337,1340,1343,1346,1349,1352,1354,1357,1360,1363,1366,1369,1372,1374,1377,1380,1383,1386,1389,1391,1394,1397,1400,1403,1406,1409,1412,1415,1418,1421,1424,1427,1430,1433,1436,1439,1442,1445,1448,1451,1454,1457,1460,1463,1466,1469,1472,1475,1478,1481,1484,1487,1490,1493,1496,1499,1502,1505,1508,1511,1513,1516,1519,1521,1524,1528,1531,1534,1537,1540,1543,1546,1549],{"id":24,"text":587,"url":24,"identifiers":1060},{"doi":587},{"id":24,"text":1062,"url":24,"identifiers":1063},"Aggarwal C. C., 2003, A framework for clustering evolving data streams. In Proceedings of the 29th International Conference on Very Large Data Bases, VLDB Endowment, 29, 81",{},{"id":24,"text":1065,"url":24,"identifiers":1066},"R. Agrawal C. Faloutsos and A. Swami. 1993. Efficient similarity search in sequence databases. Springer 69--84.   R. Agrawal C. Faloutsos and A. Swami. 1993. Efficient similarity search in sequence databases. Springer 69--84.",{"doi":1067},"10.1007\u002F3-540-57301-1_5",{"id":24,"text":1069,"url":24,"identifiers":1070},"10.1016\u002FS0196-6774(03)00085-3",{"doi":1069},{"id":24,"text":1072,"url":24,"identifiers":1073},"10.1145\u002F2424321.2424348",{"doi":1072},{"id":24,"text":1075,"url":24,"identifiers":1076},"10.1007\u002Fs10707-014-0220-8",{"doi":1075},{"id":24,"text":1078,"url":24,"identifiers":1079},"10.1145\u002F366573.366611",{"doi":1078},{"id":24,"text":1081,"url":24,"identifiers":1082},"10.1109\u002FMPRV.2003.1186725",{"doi":1081},{"id":24,"text":1084,"url":24,"identifiers":1085},"Brakatsouls S., Proceedings of the 31st International Conference on Very Large Data Bases. VLDB Endowment, 853--864",{},{"id":24,"text":1087,"url":24,"identifiers":1088},"10.1023\u002FA:1015231126594",{"doi":1087},{"id":24,"text":1090,"url":24,"identifiers":1091},"10.1109\u002FICDM.2005.95",{"doi":1090},{"id":24,"text":1093,"url":24,"identifiers":1094},"10.1109\u002FTKDE.2007.1002",{"doi":1093},{"id":24,"text":1096,"url":24,"identifiers":1097},"10.1145\u002F347090.347119",{"doi":1096},{"id":24,"text":1099,"url":24,"identifiers":1100},"10.1145\u002F1541880.1541882",{"doi":1099},{"id":24,"text":1102,"url":24,"identifiers":1103},"10.1109\u002FICDM.2012.104",{"doi":1102},{"id":24,"text":1105,"url":24,"identifiers":1106},"10.1109\u002FIVS.2007.4290280",{"doi":1105},{"id":24,"text":1108,"url":24,"identifiers":1109},"10.1145\u002F1629890.1629898",{"doi":1108},{"id":24,"text":1111,"url":24,"identifiers":1112},"Chen L., Proceedings of the 30th International Conference on Very Large Data Bases. VLDB Endowment, 792--803",{},{"id":24,"text":1114,"url":24,"identifiers":1115},"10.1145\u002F1066157.1066213",{"doi":1114},{"id":24,"text":1117,"url":24,"identifiers":1118},"10.1109\u002FICDE.2011.5767890",{"doi":1117},{"id":24,"text":1120,"url":24,"identifiers":1121},"10.1145\u002F1807167.1807197",{"doi":1120},{"id":24,"text":1123,"url":24,"identifiers":1124},"Chen W., Proceedings of the International Conference Global Navigation Satellite System. CGNS, 15--22",{},{"id":24,"text":1126,"url":24,"identifiers":1127},"10.1109\u002FICDE.2008.4497506",{"doi":1126},{"id":24,"text":1129,"url":24,"identifiers":1130},"10.1109\u002FTKDE.2004.46",{"doi":1129},{"id":24,"text":1132,"url":24,"identifiers":1133},"C. Y. Chow and M. F. Mokbel. 2011. Privacy of spatial trajectories. Computing with Spatial Trajectories Y. Zheng and X. Zhou (Eds.). Springer 109--141.  C. Y. Chow and M. F. Mokbel. 2011. Privacy of spatial trajectories. Computing with Spatial Trajectories Y. Zheng and X. Zhou (Eds.). Springer 109--141.",{"doi":1134},"10.1007\u002F978-1-4614-1629-6_4",{"id":24,"text":1136,"url":24,"identifiers":1137},"10.1109\u002FTKDE.2005.80",{"doi":1136},{"id":24,"text":1139,"url":24,"identifiers":1140},"K. Deng K. Xie K. Zheng and X. Zhou. 2011. Trajectory indexing and retrieval. Computing with Spatial Trajectories. Y. Zheng and X. Zhou (Eds.). Springer 35--60.  K. Deng K. Xie K. Zheng and X. Zhou. 2011. Trajectory indexing and retrieval. Computing with Spatial Trajectories. Y. Zheng and X. Zhou (Eds.). Springer 35--60.",{"doi":1141},"10.1007\u002F978-1-4614-1629-6_2",{"id":24,"text":1143,"url":24,"identifiers":1144},"10.3138\u002FFM57-6770-U75U-7727",{"doi":1143},{"id":24,"text":1146,"url":24,"identifiers":1147},"10.1007\u002Fs00778-009-0142-5",{"doi":1146},{"id":24,"text":1149,"url":24,"identifiers":1150},"10.1109\u002FICDE.2012.94",{"doi":1149},{"id":24,"text":1152,"url":24,"identifiers":1153},"10.1109\u002FICDM.2014.18",{"doi":1152},{"id":24,"text":1155,"url":24,"identifiers":1156},"10.1145\u002F2623330.2623675",{"doi":1155},{"id":24,"text":1158,"url":24,"identifiers":1159},"10.1145\u002F312129.312198",{"doi":1158},{"id":24,"text":853,"url":24,"identifiers":1161},{"doi":853},{"id":24,"text":614,"url":24,"identifiers":1163},{"doi":614},{"id":24,"text":1165,"url":24,"identifiers":1166},"Greenfeld J. S., 2002, Proceedings of the 81st Annual Meeting of the Transportaion Research Board. 576--582",{},{"id":24,"text":1168,"url":24,"identifiers":1169},"10.1145\u002F1183471.1183479",{"doi":1168},{"id":24,"text":1171,"url":24,"identifiers":1172},"10.1145\u002F1032222.1032259",{"doi":1171},{"id":24,"text":1174,"url":24,"identifiers":1175},"Hershberger J., Proceedings of the International Symposium on Spatial Data Handling. 134--143",{},{"id":24,"text":1177,"url":24,"identifiers":1178},"10.1109\u002FTMC.2010.62",{"doi":1177},{"id":24,"text":1180,"url":24,"identifiers":1181},"10.1109\u002FTKDE.2007.1054",{"doi":1180},{"id":24,"text":1183,"url":24,"identifiers":1184},"10.1109\u002FICDE.2008.4497588",{"doi":1183},{"id":24,"text":1186,"url":24,"identifiers":1187},"H. Jeung M. L. Yiu and C. S. Jensen. 2011. Trajectory pattern mining. Computing with Spatial Trajectories. Y. Zheng and X. Zhou (Eds.). Springer 143--177.  H. Jeung M. L. Yiu and C. S. Jensen. 2011. Trajectory pattern mining. Computing with Spatial Trajectories. Y. Zheng and X. Zhou (Eds.). Springer 143--177.",{"doi":1188},"10.1007\u002F978-1-4614-1629-6_5",{"id":24,"text":1190,"url":24,"identifiers":1191},"10.14778\u002F1453856.1453971",{"doi":1190},{"id":24,"text":1193,"url":24,"identifiers":1194},"10.1007\u002F978-3-642-02982-0_27",{"doi":1193},{"id":24,"text":1196,"url":24,"identifiers":1197},"Keogh E. J., Proceedings of the IEEE International Conference on Data Engineering. IEEE, 289--296",{},{"id":24,"text":1199,"url":24,"identifiers":1200},"A. Kharrat I. S. Popa K. Zeitouni and S. Faiz. 2008. Clustering algorithm for network constraint trajectories. Headway in Spatial Data Handling. 631--647.  A. Kharrat I. S. Popa K. Zeitouni and S. Faiz. 2008. Clustering algorithm for network constraint trajectories. Headway in Spatial Data Handling. 631--647.",{"doi":1201},"10.1007\u002F978-3-540-68566-1_36",{"id":24,"text":1203,"url":24,"identifiers":1204},"Kido H., Proceedings of the 3rd International Conference on Pervasive Services. IEEE, 88--97",{},{"id":24,"text":1206,"url":24,"identifiers":1207},"Krumm J., Trajectory analysis for driving. Computing with Spatial Trajectories",{},{"id":24,"text":1209,"url":24,"identifiers":1210},"Krumm J., Proceedings of the International Conference on Mobile and Ubiquitous Systems. IEEE, 4--13",{},{"id":24,"text":1212,"url":24,"identifiers":1213},"10.1145\u002F1247480.1247546",{"doi":1212},{"id":24,"text":1215,"url":24,"identifiers":1216},"10.1109\u002FICDE.2008.4497422",{"doi":1215},{"id":24,"text":1218,"url":24,"identifiers":1219},"W.-C. Lee and J. Krumm. 2011. Trajectory preprocessing. Computing with Spatial Trajectories Y. Zheng and X. Zhou (Eds.). Springer 1--31.  W.-C. Lee and J. Krumm. 2011. Trajectory preprocessing. Computing with Spatial Trajectories Y. Zheng and X. Zhou (Eds.). Springer 1--31.",{"doi":1220},"10.1007\u002F978-1-4614-1629-6_1",{"id":24,"text":1222,"url":24,"identifiers":1223},"10.1145\u002F1463434.1463477",{"doi":1222},{"id":24,"text":1225,"url":24,"identifiers":1226},"10.14778\u002F1920841.1920934",{"doi":1225},{"id":24,"text":1228,"url":24,"identifiers":1229},"10.1007\u002F978-3-642-12098-5_3",{"doi":1228},{"id":24,"text":1231,"url":24,"identifiers":1232},"10.1145\u002F1835804.1835942",{"doi":1231},{"id":24,"text":1234,"url":24,"identifiers":1235},"10.1145\u002F2339530.2339604",{"doi":1234},{"id":24,"text":1237,"url":24,"identifiers":1238},"Liao L., Proceedings of the National Conference on Artificial Intelligence. 348--353",{},{"id":24,"text":1240,"url":24,"identifiers":1241},"10.1145\u002F2505515.2505552",{"doi":1240},{"id":24,"text":1243,"url":24,"identifiers":1244},"10.1109\u002FTVT.2013.2272792",{"doi":1243},{"id":24,"text":1246,"url":24,"identifiers":1247},"10.1145\u002F2020408.2020571",{"doi":1246},{"id":24,"text":1249,"url":24,"identifiers":1250},"10.1145\u002F1653771.1653820",{"doi":1249},{"id":24,"text":1252,"url":24,"identifiers":1253},"10.1145\u002F2463676.2465287",{"doi":1252},{"id":24,"text":1255,"url":24,"identifiers":1256},"10.1109\u002FICDE.2013.6544843",{"doi":1255},{"id":24,"text":1258,"url":24,"identifiers":1259},"Ma S., 2015, Real-time city-scale taxi ridesharing, IEEE Transactions on Knowledge and Data Engineering 99. DOI: http:\u002F\u002Fdoi.ieeecomputersociety.org\u002F10.1109\u002FTKDE., 2014, 2334313",{},{"id":24,"text":1261,"url":24,"identifiers":1262},"Maratnia N., 2004, Proceedings of the 9th International Conference on Extending Database Technology. 765--782",{},{"id":24,"text":1264,"url":24,"identifiers":1265},"10.1559\u002F152304086783900059",{"doi":1264},{"id":24,"text":1267,"url":24,"identifiers":1268},"Mokbel M. F., Proceedings of the 23rd IEEE International Conference on Data Engineering. IEEE, 1499--1500",{},{"id":24,"text":1270,"url":24,"identifiers":1271},"Mokbel M., Proceedings of the 30th IEEE International Conference on Data Engineering, IEEE, 1246--1249",{},{"id":24,"text":1273,"url":24,"identifiers":1274},"10.1145\u002F1557019.1557091",{"doi":1273},{"id":24,"text":642,"url":24,"identifiers":1276},{"doi":642},{"id":24,"text":1278,"url":24,"identifiers":1279},"10.1145\u002F1653771.1653818",{"doi":1278},{"id":24,"text":1281,"url":24,"identifiers":1282},"10.14778\u002F2732232.2732239",{"doi":1281},{"id":24,"text":1284,"url":24,"identifiers":1285},"Ochieng W. Y., 2004, Map-matching in complex urban road networks, Brazilian Journal of Cartography, 55, 1",{},{"id":24,"text":1287,"url":24,"identifiers":1288},"10.1145\u002F2525314.2525343",{"doi":1287},{"id":24,"text":1290,"url":24,"identifiers":1291},"10.1007\u002F978-3-642-25856-5_18",{"doi":1290},{"id":24,"text":1293,"url":24,"identifiers":1294},"10.1016\u002Fj.datak.2013.05.002",{"doi":1293},{"id":24,"text":1296,"url":24,"identifiers":1297},"Patterson D. J., Proceedings of the 5th International Conference on Ubiquitous Computing. ACM, 73--89",{},{"id":24,"text":1299,"url":24,"identifiers":1300},"Pei J., Proceedings of the 29th IEEE International Conference on Data Engineering. IEEE, 215",{},{"id":24,"text":1302,"url":24,"identifiers":1303},"Pfoser D., Proceedings of the International Symposium on Advances in Spatial Databases. 111--131",{},{"id":24,"text":1305,"url":24,"identifiers":1306},"Pfoser D., Proceedings of the 26th International Conference on Very Large Data Bases. VLDB Endowment, 395--406",{},{"id":24,"text":1308,"url":24,"identifiers":1309},"Pink O., Proceedings of the 11th International IEEE Conference on Intelligent Transportation Systems. IEEE, 862--867",{},{"id":24,"text":1311,"url":24,"identifiers":1312},"10.1109\u002FSSDBM.2006.45",{"doi":1311},{"id":24,"text":1314,"url":24,"identifiers":1315},"10.1007\u002Fs10489-009-0173-z",{"doi":1314},{"id":24,"text":1317,"url":24,"identifiers":1318},"10.1080\u002F15472450600793560",{"doi":1317},{"id":24,"text":1320,"url":24,"identifiers":1321},"Richter K., 2012, Semantic trajectory compression: Representing urban movement in a nutshell, Journal of Spatial Information Science, 4, 3",{},{"id":24,"text":1323,"url":24,"identifiers":1324},"10.1007\u002Fs13218-012-0181-8",{"doi":1323},{"id":24,"text":1326,"url":24,"identifiers":1327},"10.1145\u002F2623330.2623653",{"doi":1326},{"id":24,"text":1329,"url":24,"identifiers":1330},"10.14778\u002F2732939.2732940",{"doi":1329},{"id":24,"text":1332,"url":24,"identifiers":1333},"10.1145\u002F2463676.2465303",{"doi":1332},{"id":24,"text":1335,"url":24,"identifiers":1336},"Tao Y., Proceedings of the 13th International Conference on Scientific and Statistical Database Management, 223--232",{},{"id":24,"text":1338,"url":24,"identifiers":1339},"Tao Y., Proceedings of the 27th International Conference on Very Large Data Bases. VLDB Endowment, 431--440",{},{"id":24,"text":1341,"url":24,"identifiers":1342},"Tao Y., Proceedings of the 28th International Conference on Very Large Data Bases. VLDB Endowment, 287--298",{},{"id":24,"text":1344,"url":24,"identifiers":1345},"Tang L. A., Proceedings of the 12th Symposium on Spatial and Temporal Databases. Springer, 223--241",{},{"id":24,"text":1347,"url":24,"identifiers":1348},"10.1109\u002FICDE.2012.33",{"doi":1347},{"id":24,"text":1350,"url":24,"identifiers":1351},"10.1145\u002F2542182.2542185",{"doi":1350},{"id":24,"text":657,"url":24,"identifiers":1353},{"doi":657},{"id":24,"text":1355,"url":24,"identifiers":1356},"10.1109\u002FMDM.2010.76",{"doi":1355},{"id":24,"text":1358,"url":24,"identifiers":1359},"10.1145\u002F1516360.1516460",{"doi":1358},{"id":24,"text":1361,"url":24,"identifiers":1362},"10.1145\u002F1016028.1016030",{"doi":1361},{"id":24,"text":1364,"url":24,"identifiers":1365},"10.1007\u002F11853565_13",{"doi":1364},{"id":24,"text":1367,"url":24,"identifiers":1368},"10.1109\u002FMDM.2008.24",{"doi":1367},{"id":24,"text":1370,"url":24,"identifiers":1371},"10.1145\u002F2623330.2623656",{"doi":1370},{"id":24,"text":663,"url":24,"identifiers":1373},{"doi":663},{"id":24,"text":1375,"url":24,"identifiers":1376},"10.1145\u002F1869790.1869857",{"doi":1375},{"id":24,"text":1378,"url":24,"identifiers":1379},"10.1007\u002Fs12652-012-0117-z",{"doi":1378},{"id":24,"text":1381,"url":24,"identifiers":1382},"10.1109\u002FTITS.2009.2028872",{"doi":1381},{"id":24,"text":1384,"url":24,"identifiers":1385},"10.1109\u002FICDE.2013.6544823",{"doi":1384},{"id":24,"text":1387,"url":24,"identifiers":1388},"Xu X., Proceedings of International Symposium on Spatial Data Handling. 1040--1049",{},{"id":24,"text":666,"url":24,"identifiers":1390},{"doi":666},{"id":24,"text":1392,"url":24,"identifiers":1393},"Yan X., Proceedings of the 3rd SIAM International Conference on Data Mining. IEEE, 166--177",{},{"id":24,"text":1395,"url":24,"identifiers":1396},"10.1109\u002FTKDE.2003.1198394",{"doi":1395},{"id":24,"text":1398,"url":24,"identifiers":1399},"10.1145\u002F502512.502571",{"doi":1398},{"id":24,"text":1401,"url":24,"identifiers":1402},"Yang J., Proceedings of the IEEE International Conference on Data Mining. IEEE, 725--728",{},{"id":24,"text":1404,"url":24,"identifiers":1405},"10.1109\u002FMDM.2009.11",{"doi":1404},{"id":24,"text":1407,"url":24,"identifiers":1408},"Yi B. K., Proceedings of the 14th IEEE International Conference on Data Engineering. IEEE, 201--208",{},{"id":24,"text":1410,"url":24,"identifiers":1411},"10.5555\u002F998688.1007156",{"doi":1410},{"id":24,"text":1413,"url":24,"identifiers":1414},"Yin J., Proceedings of the National Conference on Artificial Intelligence. AAAI, 578--584",{},{"id":24,"text":1416,"url":24,"identifiers":1417},"10.1007\u002Fs00779-011-0419-8",{"doi":1416},{"id":24,"text":1419,"url":24,"identifiers":1420},"Yoon H., Proceedings of the 8th IEEE International Conference on Ubiquitous Intelligence and Computing. IEEE, 19--34",{},{"id":24,"text":1422,"url":24,"identifiers":1423},"10.1145\u002F2339530.2339561",{"doi":1422},{"id":24,"text":1425,"url":24,"identifiers":1426},"10.1145\u002F1869790.1869807",{"doi":1425},{"id":24,"text":1428,"url":24,"identifiers":1429},"10.1145\u002F2020408.2020462",{"doi":1428},{"id":24,"text":1431,"url":24,"identifiers":1432},"10.1109\u002FTKDE.2011.200",{"doi":1431},{"id":24,"text":1434,"url":24,"identifiers":1435},"10.1109\u002FMDM.2010.14",{"doi":1434},{"id":24,"text":1437,"url":24,"identifiers":1438},"10.1145\u002F2030112.2030128",{"doi":1437},{"id":24,"text":1440,"url":24,"identifiers":1441},"Yuan N. J., 2012, Technical Report MSR-TR-2012-65.",{},{"id":24,"text":1443,"url":24,"identifiers":1444},"10.1109\u002FTKDE.2012.153",{"doi":1443},{"id":24,"text":1446,"url":24,"identifiers":1447},"10.1109\u002FTKDE.2014.2345405",{"doi":1446},{"id":24,"text":1449,"url":24,"identifiers":1450},"10.1145\u002F2030112.2030127",{"doi":1449},{"id":24,"text":1452,"url":24,"identifiers":1453},"10.1145\u002F2493432.2493448",{"doi":1452},{"id":24,"text":1455,"url":24,"identifiers":1456},"10.1145\u002F2644828",{"doi":1455},{"id":24,"text":1458,"url":24,"identifiers":1459},"10.1109\u002FICDE.2012.42",{"doi":1458},{"id":24,"text":1461,"url":24,"identifiers":1462},"10.1109\u002FICDE.2013.6544829",{"doi":1461},{"id":24,"text":1464,"url":24,"identifiers":1465},"10.1109\u002FTKDE.2013.160",{"doi":1464},{"id":24,"text":1467,"url":24,"identifiers":1468},"Zheng V. W., Proceedings of the 24th AAAI Conference on Artificial Intelligence. AAAI, 236--241",{},{"id":24,"text":1470,"url":24,"identifiers":1471},"10.1145\u002F1772690.1772795",{"doi":1470},{"id":24,"text":1473,"url":24,"identifiers":1474},"10.1016\u002Fj.artint.2012.02.002",{"doi":1473},{"id":24,"text":1476,"url":24,"identifiers":1477},"Zheng Y., Location-based social networks: users. Computing with Spatial Trajectories",{},{"id":24,"text":1479,"url":24,"identifiers":1480},"Zheng Y., 2012, Proceedings of the 21st International Conference on World Wide Web. ACM.",{},{"id":24,"text":1482,"url":24,"identifiers":1483},"10.1145\u002F2629592",{"doi":1482},{"id":24,"text":1485,"url":24,"identifiers":1486},"Y. Zheng X. Chen Q. Jin Y. Chen X. Qu X. Liu E. Chang W. Ma Y. Rui and W. Sun. 2014c. A Cloud-based knowledge discovery system for monitoring fine-grained air quality. MSR-TR-2014-40.  Y. Zheng X. Chen Q. Jin Y. Chen X. Qu X. Liu E. Chang W. Ma Y. Rui and W. Sun. 2014c. A Cloud-based knowledge discovery system for monitoring fine-grained air quality. MSR-TR-2014-40.",{},{"id":24,"text":1488,"url":24,"identifiers":1489},"10.1145\u002F1658373.1658374",{"doi":1488},{"id":24,"text":1491,"url":24,"identifiers":1492},"10.1109\u002FMDM.2009.50",{"doi":1491},{"id":24,"text":1494,"url":24,"identifiers":1495},"Zheng Y., Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing. ACM.",{},{"id":24,"text":1497,"url":24,"identifiers":1498},"10.1145\u002F1409635.1409677",{"doi":1497},{"id":24,"text":1500,"url":24,"identifiers":1501},"10.1145\u002F1367497.1367532",{"doi":1500},{"id":24,"text":1503,"url":24,"identifiers":1504},"10.1145\u002F2487575.2488188",{"doi":1503},{"id":24,"text":1506,"url":24,"identifiers":1507},"10.1145\u002F2632048.2632102",{"doi":1506},{"id":24,"text":1509,"url":24,"identifiers":1510},"10.1145\u002F2030112.2030126",{"doi":1509},{"id":24,"text":929,"url":24,"identifiers":1512},{"doi":929},{"id":24,"text":1514,"url":24,"identifiers":1515},"Zheng Y., 2010, GeoLife: A collaborative social networking service among user, location and trajectory, IEEE Data Engineering Bulletin, 33, 32",{},{"id":24,"text":1517,"url":24,"identifiers":1518},"10.1145\u002F1921591.1921596",{"doi":1517},{"id":24,"text":932,"url":24,"identifiers":1520},{"doi":932},{"id":24,"text":1522,"url":24,"identifiers":1523},"10.1145\u002F1653771.1653847",{"doi":1522},{"id":24,"text":1525,"url":24,"identifiers":1526},"Y. Zheng and X. Zhou. 2011. Computing with Spatial Trajectories. Springer.   Y. Zheng and X. Zhou. 2011. Computing with Spatial Trajectories. Springer.",{"doi":1527},"10.1007\u002F978-1-4614-1629-6",{"id":24,"text":1529,"url":24,"identifiers":1530},"Zhu Y., 2011, Technical Report MSR-TR-2011-144.",{},{"id":24,"text":1532,"url":24,"identifiers":1533},"GeoLife Data: http:\u002F\u002Fresearch.microsoft.com\u002Fen-us\u002Fdownloads\u002Fb16d359d-d164-469e-9fd4-daa38f2b2e13\u002Fdefault.aspx.  GeoLife Data: http:\u002F\u002Fresearch.microsoft.com\u002Fen-us\u002Fdownloads\u002Fb16d359d-d164-469e-9fd4-daa38f2b2e13\u002Fdefault.aspx.",{},{"id":24,"text":1535,"url":24,"identifiers":1536},"T-Drive Data: http:\u002F\u002Fresearch.microsoft.com\u002Fapps\u002Fpubs\u002F?id=152883.  T-Drive Data: http:\u002F\u002Fresearch.microsoft.com\u002Fapps\u002Fpubs\u002F?id=152883.",{},{"id":24,"text":1538,"url":24,"identifiers":1539},"Trajectory with transportation modes: http:\u002F\u002Fresearch.microsoft.com\u002Fapps\u002Fpubs\u002F?id=141896.  Trajectory with transportation modes: http:\u002F\u002Fresearch.microsoft.com\u002Fapps\u002Fpubs\u002F?id=141896.",{},{"id":24,"text":1541,"url":24,"identifiers":1542},"User check-in data: https:\u002F\u002Fwww.dropbox.com\u002Fs\u002F4nwb7zpsj25ibyh\u002Fcheck-in%20data.zip.  User check-in data: https:\u002F\u002Fwww.dropbox.com\u002Fs\u002F4nwb7zpsj25ibyh\u002Fcheck-in%20data.zip.",{},{"id":24,"text":1544,"url":24,"identifiers":1545},"Hurricane trajectory (HURDAT): http:\u002F\u002Fwww.nhc.noaa.gov\u002Fdata\u002Fhurdat.  Hurricane trajectory (HURDAT): http:\u002F\u002Fwww.nhc.noaa.gov\u002Fdata\u002Fhurdat.",{},{"id":24,"text":1547,"url":24,"identifiers":1548},"The Greek Trucks Dataset ” http:\u002F\u002Fwww.chorochronos.org.  The Greek Trucks Dataset ” http:\u002F\u002Fwww.chorochronos.org.",{},{"id":24,"text":1550,"url":24,"identifiers":1551},"Movebank data: https:\u002F\u002Fwww.movebank.org\u002F.  Movebank data: https:\u002F\u002Fwww.movebank.org\u002F.",{},{"id":1553,"createTime":1554,"updateTime":1554,"relativeEntities":1555,"slug":1556,"properties":1557,"entityType":136,"verifyStatus":137,"verifyTime":1554,"verifyNote":139,"languages":1568,"translateLanguages":24,"viewCount":25,"primaryUrl":1569,"fullTextUrl":24,"authors":1570,"publicationType":225,"publisherRelationship":1700,"citationCount":111,"citationInfo":1755,"publishDate":1759,"publishYear":1756,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":1760,"openAccess":24,"references":1761,"isForceReanalyzing":409},"f1df841d-b5b9-486b-b886-cba2d77dac5d","2024-10-15T11:40:05.987+00:00",[],"Self-weighted-Robust-LDA-for-Multiclass-Classification-with-Edge-Classes",{"openalex":1558,"mag":1560,"abstract":1562,"title":1564,"doi":1566},{"VOID":1559},"W3117488606",{"VOID":1561},"3117488606",{"EN":1563},"\u003Cjats:p>Linear discriminant analysis (LDA) is a popular technique to learn the most discriminative features for multi-class classification. A vast majority of existing LDA algorithms are prone to be dominated by the class with very large deviation from the others, i.e., edge class, which occurs frequently in multi-class classification. First, the existence of edge classes often makes the total mean biased in the calculation of between-class scatter matrix. Second, the exploitation of ℓ\u003Cjats:sub>2\u003C\u002Fjats:sub>-norm based between-class distance criterion magnifies the extremely large distance corresponding to edge class. In this regard, a novel self-weighted robust LDA with ℓ\u003Cjats:sub>2,1\u003C\u002Fjats:sub>-norm based pairwise between-class distance criterion, called SWRLDA, is proposed for multi-class classification especially with edge classes. SWRLDA can automatically avoid the optimal mean calculation and simultaneously learn adaptive weights for each class pair without setting any additional parameter. An efficient re-weighted algorithm is exploited to derive the global optimum of the challenging ℓ\u003Cjats:sub>2,1\u003C\u002Fjats:sub>-norm maximization problem. The proposed SWRLDA is easy to implement and converges fast in practice. Extensive experiments demonstrate that SWRLDA performs favorably against other compared methods on both synthetic and real-world datasets while presenting superior computational efficiency in comparison with other techniques.\u003C\u002Fjats:p>",{"EN":1565},"Self-weighted Robust LDA for Multiclass Classification with Edge Classes",{"VOID":1567},"10.1145\u002F3418284",[141],"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002F10.1145\u002F3418284",[1571,1590,1609,1626,1643,1662,1681],{"id":1572,"sortIndex":25,"researcher":24,"roles":1573,"affiliations":1574,"properties":1583},"902b6019-df7b-4370-8f34-2700b07d1d79",[],[1575],{"id":1576,"sortIndex":25,"affiliation":1577,"properties":24},"11a71412-348e-4e92-b5ce-c2e5bd215862",{"id":1576,"createTime":24,"updateTime":24,"relativeEntities":1578,"slug":24,"properties":1579,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1582,"statistic":24},[],{"title":1580},{"EN":1581},"School of Electronic and Information Engineering, Xi’an Jiaotong University, Shaanxi, China",[],{"orcid":1584,"title":1586,"openalex":1588},{"VOID":1585},"https:\u002F\u002Forcid.org\u002F0000-0003-2595-0398",{"EN":1587},"Caixia Yan",{"VOID":1589},"A5063081769",{"id":1591,"sortIndex":105,"researcher":24,"roles":1592,"affiliations":1593,"properties":1602},"76c38689-234a-4c39-b177-450d795cb7af",[],[1594],{"id":1595,"sortIndex":25,"affiliation":1596,"properties":24},"3f22422d-83aa-47d3-973e-552fd54863f4",{"id":1595,"createTime":24,"updateTime":24,"relativeEntities":1597,"slug":24,"properties":1598,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1601,"statistic":24},[],{"title":1599},{"VI":1600},"Faculty of Information Technology, Monash University, Australia",[],{"orcid":1603,"title":1605,"openalex":1607},{"VOID":1604},"https:\u002F\u002Forcid.org\u002F0000-0002-7778-8807",{"EN":1606},"Xiaojun Chang",{"VOID":1608},"A5034967388",{"id":1610,"sortIndex":102,"researcher":24,"roles":1611,"affiliations":1612,"properties":1619},"e9f33a56-9e09-4684-b1e7-50ab1a0dc653",[],[1613],{"id":1576,"sortIndex":25,"affiliation":1614,"properties":24},{"id":1576,"createTime":24,"updateTime":24,"relativeEntities":1615,"slug":24,"properties":1616,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1618,"statistic":24},[],{"title":1617},{"EN":1581},[],{"orcid":1620,"title":1622,"openalex":1624},{"VOID":1621},"https:\u002F\u002Forcid.org\u002F0000-0002-0140-7860",{"EN":1623},"Minnan Luo",{"VOID":1625},"A5013911439",{"id":1627,"sortIndex":205,"researcher":24,"roles":1628,"affiliations":1629,"properties":1636},"e341a67d-5f50-45e2-9847-98b5b655d5fa",[],[1630],{"id":1576,"sortIndex":25,"affiliation":1631,"properties":24},{"id":1576,"createTime":24,"updateTime":24,"relativeEntities":1632,"slug":24,"properties":1633,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1635,"statistic":24},[],{"title":1634},{"EN":1581},[],{"orcid":1637,"title":1639,"openalex":1641},{"VOID":1638},"https:\u002F\u002Forcid.org\u002F0000-0002-8436-4754",{"EN":1640},"Qinghua Zheng",{"VOID":1642},"A5041083459",{"id":1644,"sortIndex":97,"researcher":24,"roles":1645,"affiliations":1646,"properties":1655},"2146bbe3-1b24-4543-aa4a-1d5f9d7e599a",[],[1647],{"id":1648,"sortIndex":25,"affiliation":1649,"properties":24},"a5524ca3-3e34-49f5-88b1-f080a10f58f5",{"id":1648,"createTime":24,"updateTime":24,"relativeEntities":1650,"slug":24,"properties":1651,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1654,"statistic":24},[],{"title":1652},{"VI":1653},"College of Computer Science and Artificial Intelligence, Wenzhou University, China",[],{"orcid":1656,"title":1658,"openalex":1660},{"VOID":1657},"https:\u002F\u002Forcid.org\u002F0000-0003-0958-7285",{"EN":1659},"Xiaoqin Zhang",{"VOID":1661},"A5100699785",{"id":1663,"sortIndex":101,"researcher":24,"roles":1664,"affiliations":1665,"properties":1674},"f94cb9e3-9d62-44da-bf6f-d93d5a4cc6cf",[],[1666],{"id":1667,"sortIndex":25,"affiliation":1668,"properties":24},"50a11d95-2c2a-40e8-aba0-1bc0ea620bb3",{"id":1667,"createTime":24,"updateTime":24,"relativeEntities":1669,"slug":24,"properties":1670,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1673,"statistic":24},[],{"title":1671},{"EN":1672},"Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, China",[],{"orcid":1675,"title":1677,"openalex":1679},{"VOID":1676},"https:\u002F\u002Forcid.org\u002F0000-0001-9642-8009",{"EN":1678},"Zhihui Li",{"VOID":1680},"A5100461813",{"id":1682,"sortIndex":103,"researcher":24,"roles":1683,"affiliations":1684,"properties":1693},"fee9eb96-e3dc-4be8-8007-4d724b268d96",[],[1685],{"id":1686,"sortIndex":25,"affiliation":1687,"properties":24},"1f08825b-ffb4-4486-b219-bb6cda9479d2",{"id":1686,"createTime":24,"updateTime":24,"relativeEntities":1688,"slug":24,"properties":1689,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1692,"statistic":24},[],{"title":1690},{"EN":1691},"Center for Optical Image Analysis and Learning, Northwestern Polytechnical University, Shaanxi, China",[],{"orcid":1694,"title":1696,"openalex":1698},{"VOID":1695},"https:\u002F\u002Forcid.org\u002F0000-0002-0871-6519",{"EN":1697},"Feiping Nie",{"VOID":1699},"A5003222421",{"url":24,"publisher":1701,"properties":1748},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1702,"slug":10,"properties":1703,"entityType":22,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":25,"subjectFields":1708,"manageAffiliations":1717,"indexDatabases":1728,"url":90,"thumbnailPath":24,"statistic":1743,"gsStatistic":24,"type":24,"analyzePriority":24},[],{"country":1704,"eissn":1705,"issn":1706,"title":1707},{"VOID":13},{"VOID":15},{"VOID":17},{"EN":19},[1709,1713],{"id":28,"createTime":24,"updateTime":24,"relativeEntities":1710,"label":1711,"description":1712,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":31},{},{"id":34,"createTime":24,"updateTime":24,"relativeEntities":1714,"label":1715,"description":1716,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":37},{},[1718,1723],{"id":41,"createTime":24,"updateTime":24,"relativeEntities":1719,"slug":24,"properties":1720,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1722,"statistic":24},[],{"title":1721},{"EN":45},[],{"id":48,"createTime":24,"updateTime":24,"relativeEntities":1724,"slug":24,"properties":1725,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1727,"statistic":24},[],{"title":1726},{"EN":52},[],[1729,1736],{"id":56,"indexDatabase":1730,"url":69,"indexYears":24,"academicFieldIds":1735,"indexDatabaseRanking":24},{"id":58,"createTime":24,"updateTime":24,"relativeEntities":1731,"label":1732,"description":1733,"key":65,"publicationTags":1734,"standard":24},[],{"EN":61,"VI":61},{"EN":63,"VI":64},[67,68],[71],{"id":73,"indexDatabase":1737,"url":84,"indexYears":85,"academicFieldIds":1742,"indexDatabaseRanking":89},{"id":75,"createTime":24,"updateTime":24,"relativeEntities":1738,"label":1739,"description":1740,"key":81,"publicationTags":1741,"standard":24},[],{"EN":78,"VI":78},{"EN":78,"VI":80},[83],[87,88],{"impactFactor":25,"impactFactorByYear":1744,"i10Index":101,"i10IndexLast5Year":102,"totalPublication":103,"totalPublicationByYear":1745,"totalCitation":106,"totalCitationByYear":1746,"totalCitationPerPublication":112,"totalCitationPerPublicationByYear":1747,"hindexLast5Year":101,"hindex":101},{"2012":93,"2013":94,"2016":95,"2017":96,"2020":97,"2021":98,"2022":99,"2023":100},{"2011":105,"2015":102,"2019":105,"2021":105},{"2011":108,"2015":109,"2019":110,"2021":111},{"2011":108,"2015":114,"2019":110,"2021":111},{"issue":1749,"pages":1751,"volume":1753},{"VOID":1750},"1",{"VOID":1752},"1-19",{"VOID":1754},"12",{"total":111,"publishYear":1756,"statisticByYear":1757},2021,{"2021":100,"2022":99,"2023":100,"2024":1758},9,"2021-02-28",[67,89],[1762,1765,1768,1771,1774,1777,1780,1783,1786,1790,1793,1796,1799,1802,1805,1808,1811,1814,1817,1820,1823,1826,1829,1832,1835,1838,1841,1844,1847,1850,1853,1856,1859,1862,1865,1868,1872,1875,1879,1882,1885,1888,1891,1894,1897,1900,1903,1906,1909,1912,1915,1918,1921,1924,1927,1930,1933,1936,1939,1942,1945,1948,1951,1954,1957],{"id":24,"text":1763,"url":24,"identifiers":1764},"Abou-Moustafa Karim T., Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.",{},{"id":24,"text":1766,"url":24,"identifiers":1767},"Bian Wei, 2008, Proceedings of the International Conference on Pattern Recognition.",{},{"id":24,"text":1769,"url":24,"identifiers":1770},"10.1109\u002FTPAMI.2010.189",{"doi":1769},{"id":24,"text":1772,"url":24,"identifiers":1773},"C. L. Blake and C. J. Merz. 1998. UCI Repository of Machine Learning Databases. Department of Information and Computer Science University of California Irvine CA. C. L. Blake and C. J. Merz. 1998. UCI Repository of Machine Learning Databases. Department of Information and Computer Science University of California Irvine CA.",{},{"id":24,"text":1775,"url":24,"identifiers":1776},"10.1109\u002FTKDE.2007.190669",{"doi":1775},{"id":24,"text":1778,"url":24,"identifiers":1779},"10.1145\u002F1961189.1961199",{"doi":1778},{"id":24,"text":1781,"url":24,"identifiers":1782},"Chang Xiaojun, Proceedings of the European Conference on Computer Vision, Vittorio Ferrari, Martial Hebert, Cristian Sminchisescu, and Yair Weiss (Eds.).",{},{"id":24,"text":1784,"url":24,"identifiers":1785},"Chang Xiaojun, 2015, Proceedings of the AAAI Conference on Artificial Intelligence, Blai Bonet and Sven Koenig (Eds.).",{},{"id":24,"text":1787,"url":24,"identifiers":1788},"Xiaojun Chang Haoquan Shen Sen Wang Jiajun Liu and Xue Li. 2014. Semi-supervised feature analysis for multimedia annotation by mining label correlation. In Proceedings of the 18th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (Lecture Notes in Computer Science) Vincent S. Tseng Tu Bao Ho Zhi-Hua Zhou Arbee L. P. Chen and Hung-Yu Kao (Eds.) Vol. 8444. Springer 74--85. Xiaojun Chang Haoquan Shen Sen Wang Jiajun Liu and Xue Li. 2014. Semi-supervised feature analysis for multimedia annotation by mining label correlation. In Proceedings of the 18th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (Lecture Notes in Computer Science) Vincent S. Tseng Tu Bao Ho Zhi-Hua Zhou Arbee L. P. Chen and Hung-Yu Kao (Eds.) Vol. 8444. Springer 74--85.",{"doi":1789},"10.1007\u002F978-3-319-06605-9_7",{"id":24,"text":1791,"url":24,"identifiers":1792},"10.1109\u002FTNNLS.2016.2582746",{"doi":1791},{"id":24,"text":1794,"url":24,"identifiers":1795},"Chang Xiaojun, Proceedings of the Conference on Computer Vision and Pattern Recognition.",{},{"id":24,"text":1797,"url":24,"identifiers":1798},"10.24963\u002Fijcai.2017\u002F134",{"doi":1797},{"id":24,"text":1800,"url":24,"identifiers":1801},"10.1016\u002Fj.patcog.2018.05.007",{"doi":1800},{"id":24,"text":1803,"url":24,"identifiers":1804},"10.1016\u002F0375-6742(92)90105-H",{"doi":1803},{"id":24,"text":1806,"url":24,"identifiers":1807},"10.5555\u002F1059467.1059472",{"doi":1806},{"id":24,"text":1809,"url":24,"identifiers":1810},"Fanty Mark, 1991, Proceedings of the Conference on Neural Information Processing Systems.",{},{"id":24,"text":1812,"url":24,"identifiers":1813},"10.1016\u002Fj.eswa.2013.08.089",{"doi":1812},{"id":24,"text":1815,"url":24,"identifiers":1816},"Fukunaga Keinosuke, Introduction to Statistical Pattern Recognition",{},{"id":24,"text":1818,"url":24,"identifiers":1819},"10.1109\u002F34.927464",{"doi":1818},{"id":24,"text":1821,"url":24,"identifiers":1822},"10.1109\u002FTCYB.2017.2773562",{"doi":1821},{"id":24,"text":1824,"url":24,"identifiers":1825},"10.1109\u002FCVPR.2018.00946",{"doi":1824},{"id":24,"text":1827,"url":24,"identifiers":1828},"10.1006\u002Fjmva.1999.1857",{"doi":1827},{"id":24,"text":1830,"url":24,"identifiers":1831},"10.1007\u002F3-540-36755-1_14",{"doi":1830},{"id":24,"text":1833,"url":24,"identifiers":1834},"10.1016\u002FS0167-9473(02)00299-2",{"doi":1833},{"id":24,"text":1836,"url":24,"identifiers":1837},"10.1109\u002FTNNLS.2013.2258937",{"doi":1836},{"id":24,"text":1839,"url":24,"identifiers":1840},"10.5555\u002F3091622.3091662",{"doi":1839},{"id":24,"text":1842,"url":24,"identifiers":1843},"10.1109\u002FTNNLS.2018.2817538",{"doi":1842},{"id":24,"text":1845,"url":24,"identifiers":1846},"10.1109\u002FTKDE.2017.2728531",{"doi":1845},{"id":24,"text":1848,"url":24,"identifiers":1849},"10.1109\u002FACCESS.2018.2859299",{"doi":1848},{"id":24,"text":1851,"url":24,"identifiers":1852},"10.1109\u002F34.935849",{"doi":1851},{"id":24,"text":1854,"url":24,"identifiers":1855},"10.1109\u002FTCYB.2017.2647904",{"doi":1854},{"id":24,"text":1857,"url":24,"identifiers":1858},"Luo Minnan, 2016, Proceedings of the International Joint Conference on Artificial Intelligence, Subbarao Kambhampati (Ed.).",{},{"id":24,"text":1860,"url":24,"identifiers":1861},"10.1109\u002FTNNLS.2017.2650978",{"doi":1860},{"id":24,"text":1863,"url":24,"identifiers":1864},"Douglas Martin R., 2006, Yohai",{},{"id":24,"text":1866,"url":24,"identifiers":1867},"10.1109\u002FTCYB.2016.2577590",{"doi":1866},{"id":24,"text":1869,"url":24,"identifiers":1870},"Peng Chong, 2016, A supervised learning model for high-dimensional and large-scale data, ACM Trans. Intell. Syst. Technol., 8, 1, 10.1145\u002F2972957",{"doi":1871},"10.1145\u002F2972957",{"id":24,"text":1873,"url":24,"identifiers":1874},"Peng Chong, 2019, Discriminative ridge machine: A classifier for high-dimensional data or imbalanced data. arXiv preprint arXiv:1904.07496",{},{"id":24,"text":1876,"url":24,"identifiers":1877},"Rao C. Radhakrishna, 1948, The utilization of multiple measurements in problems of biological classification, J. Royal Stat. Soc., 10, 159, 10.1111\u002Fj.2517-6161.1948.tb00008.x",{"doi":1878},"10.1111\u002Fj.2517-6161.1948.tb00008.x",{"id":24,"text":1880,"url":24,"identifiers":1881},"10.5555\u002F874061.875452",{"doi":1880},{"id":24,"text":1883,"url":24,"identifiers":1884},"Gilbert W. Stewart. 2001. Eigensystem. Society for Industrial 8 Applied Mathematics. Gilbert W. Stewart. 2001. Eigensystem. Society for Industrial 8 Applied Mathematics.",{},{"id":24,"text":1886,"url":24,"identifiers":1887},"10.1109\u002FTPAMI.2008.70",{"doi":1886},{"id":24,"text":1889,"url":24,"identifiers":1890},"10.1007\u002Fs13042-016-0540-0",{"doi":1889},{"id":24,"text":1892,"url":24,"identifiers":1893},"10.1016\u002Fj.sigpro.2014.12.012",{"doi":1892},{"id":24,"text":1895,"url":24,"identifiers":1896},"10.1109\u002FTCSVT.2018.2799214",{"doi":1895},{"id":24,"text":1898,"url":24,"identifiers":1899},"10.1145\u002F2956556",{"doi":1898},{"id":24,"text":1901,"url":24,"identifiers":1902},"10.1145\u002F3007195",{"doi":1901},{"id":24,"text":1904,"url":24,"identifiers":1905},"10.1109\u002FICPR.2010.144",{"doi":1904},{"id":24,"text":1907,"url":24,"identifiers":1908},"Xue Xiaowei, 2017, In Proceedings of the AAAI Conference on Artificial Intelligence, Satinder P. Singh and Shaul Markovitch (Eds.).",{},{"id":24,"text":1910,"url":24,"identifiers":1911},"Syed Yahaya Sharipah Soaad, 2016, Robust linear discriminant analysis with automatic trimmed mean, J. Telecommun. Electron. Comput. Eng., 8, 1",{},{"id":24,"text":1913,"url":24,"identifiers":1914},"10.1016\u002Fj.ins.2017.08.004",{"doi":1913},{"id":24,"text":1916,"url":24,"identifiers":1917},"10.1145\u002F1273496.1273633",{"doi":1916},{"id":24,"text":1919,"url":24,"identifiers":1920},"10.1109\u002FTKDE.2006.160",{"doi":1919},{"id":24,"text":1922,"url":24,"identifiers":1923},"10.1145\u002F1143844.1143979",{"doi":1922},{"id":24,"text":1925,"url":24,"identifiers":1926},"10.1016\u002Fj.patcog.2010.09.019",{"doi":1925},{"id":24,"text":1928,"url":24,"identifiers":1929},"10.1109\u002FTIP.2017.2685343",{"doi":1928},{"id":24,"text":1931,"url":24,"identifiers":1932},"Zhang Liang, Proceedings of the International Conference on Acoustics, Speech and Signal Processing.",{},{"id":24,"text":1934,"url":24,"identifiers":1935},"10.1007\u002F978-3-540-88682-2_55",{"doi":1934},{"id":24,"text":1937,"url":24,"identifiers":1938},"10.1109\u002FTNNLS.2020.3009209",{"doi":1937},{"id":24,"text":1940,"url":24,"identifiers":1941},"10.1109\u002FICFHR.2012.196",{"doi":1940},{"id":24,"text":1943,"url":24,"identifiers":1944},"Zhang Yu, 2010, Proceedings of the Conference on Neural Information Processing Systems.",{},{"id":24,"text":1946,"url":24,"identifiers":1947},"10.1162\u002Fneco_a_01116",{"doi":1946},{"id":24,"text":1949,"url":24,"identifiers":1950},"10.1109\u002FTKDE.2018.2842023",{"doi":1949},{"id":24,"text":1952,"url":24,"identifiers":1953},"10.1162\u002FNECO_a_00950",{"doi":1952},{"id":24,"text":1955,"url":24,"identifiers":1956},"10.1109\u002FTCYB.2016.2529299",{"doi":1955},{"id":24,"text":1958,"url":24,"identifiers":1959},"Zhu Lei, Proceedings of the ACM International Conference on Multimedia, Qiong Liu, Rainer Lienhart, Haohong Wang, Sheng-Wei “Kuan-Ta",{},{"id":1961,"createTime":1962,"updateTime":1962,"relativeEntities":1963,"slug":1964,"properties":1965,"entityType":136,"verifyStatus":137,"verifyTime":1962,"verifyNote":139,"languages":1976,"translateLanguages":24,"viewCount":25,"primaryUrl":1977,"fullTextUrl":24,"authors":1978,"publicationType":225,"publisherRelationship":2049,"citationCount":2103,"citationInfo":2104,"publishDate":2108,"publishYear":1045,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":2109,"openAccess":24,"references":2110,"isForceReanalyzing":409},"5fe8da62-6c17-45d8-bc14-83b8f9f3f746","2024-10-05T03:03:47.842+00:00",[],"Extracting-City-Traffic-Events-from-Social-Streams",{"openalex":1966,"mag":1968,"abstract":1970,"title":1972,"doi":1974},{"VOID":1967},"W1892832513",{"VOID":1969},"1892832513",{"EN":1971},"\u003Cjats:p>Cities are composed of complex systems with physical, cyber, and social components. Current works on extracting and understanding city events mainly rely on technology-enabled infrastructure to observe and record events. In this work, we propose an approach to leverage citizen observations of various city systems and services, such as traffic, public transport, water supply, weather, sewage, and public safety, as a source of city events. We investigate the feasibility of using such textual streams for extracting city events from annotated text. We formalize the problem of annotating social streams such as microblogs as a sequence labeling problem. We present a novel training data creation process for training sequence labeling models. Our automatic training data creation process utilizes instance-level domain knowledge (e.g., locations in a city, possible event terms). We compare this automated annotation process to a state-of-the-art tool that needs manually created training data and show that it has comparable performance in annotation tasks. An aggregation algorithm is then presented for event extraction from annotated text. We carry out a comprehensive evaluation of the event annotation and event extraction on a real-world dataset consisting of event reports and tweets collected over 4 months from the San Francisco Bay Area. The evaluation results are promising and provide insights into the utility of social stream for extracting city events.\u003C\u002Fjats:p>",{"EN":1973},"Extracting City Traffic Events from Social Streams",{"VOID":1975},"10.1145\u002F2717317",[141],"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002F10.1145\u002F2717317",[1979,1996,2015,2032],{"id":1980,"sortIndex":25,"researcher":24,"roles":1981,"affiliations":1982,"properties":1991},"f32834a6-a8b8-47fb-aa51-f2ae768a5546",[],[1983],{"id":1984,"sortIndex":25,"affiliation":1985,"properties":24},"fbbe83b4-d47c-47ec-a68f-c0669926de23",{"id":1984,"createTime":24,"updateTime":24,"relativeEntities":1986,"slug":24,"properties":1987,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1990,"statistic":24},[],{"title":1988},{"EN":1989},"Wright State University, OH",[],{"title":1992,"openalex":1994},{"EN":1993},"Pramod Anantharam",{"VOID":1995},"A5010060555",{"id":1997,"sortIndex":105,"researcher":24,"roles":1998,"affiliations":1999,"properties":2008},"9cbb9bbb-f02f-4e1d-9714-3109ccaea221",[],[2000],{"id":2001,"sortIndex":25,"affiliation":2002,"properties":24},"4cf6a176-bcb0-44e3-9d0d-e3ef3311dad4",{"id":2001,"createTime":24,"updateTime":24,"relativeEntities":2003,"slug":24,"properties":2004,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2007,"statistic":24},[],{"title":2005},{"VI":2006},"University of Surrey, Guildford, UK",[],{"orcid":2009,"title":2011,"openalex":2013},{"VOID":2010},"https:\u002F\u002Forcid.org\u002F0000-0001-8591-9638",{"EN":2012},"Payam Barnaghi",{"VOID":2014},"A5056157061",{"id":2016,"sortIndex":102,"researcher":24,"roles":2017,"affiliations":2018,"properties":2025},"9d23bb8b-77fe-4523-ab07-4283fd85519c",[],[2019],{"id":1984,"sortIndex":25,"affiliation":2020,"properties":24},{"id":1984,"createTime":24,"updateTime":24,"relativeEntities":2021,"slug":24,"properties":2022,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2024,"statistic":24},[],{"title":2023},{"EN":1989},[],{"orcid":2026,"title":2028,"openalex":2030},{"VOID":2027},"https:\u002F\u002Forcid.org\u002F0000-0002-7041-6963",{"EN":2029},"Krishnaprasad Thirunarayan",{"VOID":2031},"A5060617658",{"id":2033,"sortIndex":205,"researcher":24,"roles":2034,"affiliations":2035,"properties":2042},"a9b29d99-125f-45a3-b9db-5b166c7c6d14",[],[2036],{"id":1984,"sortIndex":25,"affiliation":2037,"properties":24},{"id":1984,"createTime":24,"updateTime":24,"relativeEntities":2038,"slug":24,"properties":2039,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2041,"statistic":24},[],{"title":2040},{"EN":1989},[],{"orcid":2043,"title":2045,"openalex":2047},{"VOID":2044},"https:\u002F\u002Forcid.org\u002F0000-0002-0021-5293",{"EN":2046},"Amit Sheth",{"VOID":2048},"A5028772801",{"url":24,"publisher":2050,"properties":2097},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":2051,"slug":10,"properties":2052,"entityType":22,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":25,"subjectFields":2057,"manageAffiliations":2066,"indexDatabases":2077,"url":90,"thumbnailPath":24,"statistic":2092,"gsStatistic":24,"type":24,"analyzePriority":24},[],{"country":2053,"eissn":2054,"issn":2055,"title":2056},{"VOID":13},{"VOID":15},{"VOID":17},{"EN":19},[2058,2062],{"id":28,"createTime":24,"updateTime":24,"relativeEntities":2059,"label":2060,"description":2061,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":31},{},{"id":34,"createTime":24,"updateTime":24,"relativeEntities":2063,"label":2064,"description":2065,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":37},{},[2067,2072],{"id":41,"createTime":24,"updateTime":24,"relativeEntities":2068,"slug":24,"properties":2069,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2071,"statistic":24},[],{"title":2070},{"EN":45},[],{"id":48,"createTime":24,"updateTime":24,"relativeEntities":2073,"slug":24,"properties":2074,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2076,"statistic":24},[],{"title":2075},{"EN":52},[],[2078,2085],{"id":56,"indexDatabase":2079,"url":69,"indexYears":24,"academicFieldIds":2084,"indexDatabaseRanking":24},{"id":58,"createTime":24,"updateTime":24,"relativeEntities":2080,"label":2081,"description":2082,"key":65,"publicationTags":2083,"standard":24},[],{"EN":61,"VI":61},{"EN":63,"VI":64},[67,68],[71],{"id":73,"indexDatabase":2086,"url":84,"indexYears":85,"academicFieldIds":2091,"indexDatabaseRanking":89},{"id":75,"createTime":24,"updateTime":24,"relativeEntities":2087,"label":2088,"description":2089,"key":81,"publicationTags":2090,"standard":24},[],{"EN":78,"VI":78},{"EN":78,"VI":80},[83],[87,88],{"impactFactor":25,"impactFactorByYear":2093,"i10Index":101,"i10IndexLast5Year":102,"totalPublication":103,"totalPublicationByYear":2094,"totalCitation":106,"totalCitationByYear":2095,"totalCitationPerPublication":112,"totalCitationPerPublicationByYear":2096,"hindexLast5Year":101,"hindex":101},{"2012":93,"2013":94,"2016":95,"2017":96,"2020":97,"2021":98,"2022":99,"2023":100},{"2011":105,"2015":102,"2019":105,"2021":105},{"2011":108,"2015":109,"2019":110,"2021":111},{"2011":108,"2015":114,"2019":110,"2021":111},{"issue":2098,"pages":2100,"volume":2102},{"VOID":2099},"4",{"VOID":2101},"1-27",{"VOID":1042},90,{"total":2103,"publishYear":1045,"statisticByYear":2105},{"2014":102,"2015":205,"2016":2106,"2017":1758,"2018":2107,"2019":2107,"2020":97,"2021":816,"2022":103,"2023":103,"2024":205},16,15,"2015-08-13",[67,89],[2111,2114,2117,2120,2123,2126,2129,2132,2135,2139,2142,2145,2148,2151,2154,2157,2160,2163,2166,2169,2172,2175,2178,2181,2184,2187,2190,2193,2196,2199,2202,2205,2208,2211,2214,2217,2220,2223],{"id":24,"text":2112,"url":24,"identifiers":2113},"Charu, 2012, Aggarwal and Karthik Subbian",{},{"id":24,"text":2115,"url":24,"identifiers":2116},"2008, Retrieved",{},{"id":24,"text":2118,"url":24,"identifiers":2119},"Anantharam Pramod, 2013, Proceedings of the 20th ITS World Congress.",{},{"id":24,"text":2121,"url":24,"identifiers":2122},"Becker Hila, 2011, Proceedings of the 5th International AAAI Conference on Weblogs and Social Media.",{},{"id":24,"text":2124,"url":24,"identifiers":2125},"Bélissent Jennifer, 2010, Retrieved",{},{"id":24,"text":2127,"url":24,"identifiers":2128},"Bélissent Jennifer, 2013, Retrieved",{},{"id":24,"text":2130,"url":24,"identifiers":2131},"Burke Jeffrey A., Proceedings of the World Sensor Web Workshop (Sensys’06)",{},{"id":24,"text":2133,"url":24,"identifiers":2134},"Chen Edwin, 2012, Retrieved",{},{"id":24,"text":2136,"url":24,"identifiers":2137},"Commentz-Walter Beate, A String Matching Algorithm Fast on the Average, 10.1007\u002F3-540-09510-1_10",{"doi":2138},"10.1007\u002F3-540-09510-1_10",{"id":24,"text":2140,"url":24,"identifiers":2141},"Dou Wenwen, 2012, Proceedings of the IEEE VisWeek Workshop on Interactive Visual Text Analytics--Task Driven Analytics of Social Media Content. 971--980",{},{"id":24,"text":2143,"url":24,"identifiers":2144},"Elkan Charles, 2008, Retrieved",{},{"id":24,"text":2146,"url":24,"identifiers":2147},"10.1109\u002FSENSORCOMM.2010.50",{"doi":2146},{"id":24,"text":2149,"url":24,"identifiers":2150},"10.5555\u002F1289189.1289229",{"doi":2149},{"id":24,"text":2152,"url":24,"identifiers":2153},"10.1109\u002FMPRV.2008.80",{"doi":2152},{"id":24,"text":2155,"url":24,"identifiers":2156},"Kehoe Michael, 2011, Retrieved",{},{"id":24,"text":2158,"url":24,"identifiers":2159},"Koller Daphne, Probabilistic Graphical Models: Principles and Techniques",{},{"id":24,"text":2161,"url":24,"identifiers":2162},"10.1145\u002F1008992.1009044",{"doi":2161},{"id":24,"text":2164,"url":24,"identifiers":2165},"10.1145\u002F1772690.1772751",{"doi":2164},{"id":24,"text":2167,"url":24,"identifiers":2168},"Lafferty John, Proceedings of the 18th International Conference on Machine Learning (ICML’01)",{},{"id":24,"text":2170,"url":24,"identifiers":2171},"10.1145\u002F2337542.2337557",{"doi":2170},{"id":24,"text":2173,"url":24,"identifiers":2174},"Lindsay Greg, 2010, Retrieved",{},{"id":24,"text":2176,"url":24,"identifiers":2177},"10.1007\u002F978-3-540-88906-9_26",{"doi":2176},{"id":24,"text":2179,"url":24,"identifiers":2180},"10.1145\u002F1869983.1870005",{"doi":2179},{"id":24,"text":2182,"url":24,"identifiers":2183},"10.1162\u002Fcoli.2008.34.2.145",{"doi":2182},{"id":24,"text":2185,"url":24,"identifiers":2186},"McCallum Andrew Kachites, 2002, Mallet: Machine Learning for Language Toolkit.",{},{"id":24,"text":2188,"url":24,"identifiers":2189},"Mladenić Dunja, 2012, Retrieved",{},{"id":24,"text":2191,"url":24,"identifiers":2192},"10.1007\u002F978-3-642-04409-0_52",{"doi":2191},{"id":24,"text":2194,"url":24,"identifiers":2195},"10.1109\u002FMC.2011.187",{"doi":2194},{"id":24,"text":2197,"url":24,"identifiers":2198},"Naughton Martina, 2006, Proceedings of the AAAI Workshop on Event Extraction and Synthesis. 1--6.",{},{"id":24,"text":2200,"url":24,"identifiers":2201},"10.1007\u002F978-3-642-04769-5_16",{"doi":2200},{"id":24,"text":2203,"url":24,"identifiers":2204},"10.5038\u002F2375-0901.7.3.5",{"doi":2203},{"id":24,"text":2206,"url":24,"identifiers":2207},"Ramshaw Lance A., 1999, Marcus",{},{"id":24,"text":2209,"url":24,"identifiers":2210},"10.1145\u002F2339530.2339704",{"doi":2209},{"id":24,"text":2212,"url":24,"identifiers":2213},"10.1145\u002F1772690.1772777",{"doi":2212},{"id":24,"text":2215,"url":24,"identifiers":2216},"Sayyadi Hassan, 2009, Proceedings of the 3rd International AAAI Conference on Weblogs and Social Media (ICWSM’09)",{},{"id":24,"text":2218,"url":24,"identifiers":2219},"10.1109\u002FMIC.2009.77",{"doi":2218},{"id":24,"text":2221,"url":24,"identifiers":2222},"10.1007\u002F978-3-540-69858-6_21",{"doi":2221},{"id":24,"text":2224,"url":24,"identifiers":2225},"10.1007\u002F978-3-642-29047-3_28",{"doi":2224},{"id":2227,"createTime":2228,"updateTime":2228,"relativeEntities":2229,"slug":2230,"properties":2231,"entityType":136,"verifyStatus":137,"verifyTime":2228,"verifyNote":139,"languages":2240,"translateLanguages":24,"viewCount":25,"primaryUrl":2241,"fullTextUrl":24,"authors":2242,"publicationType":225,"publisherRelationship":2277,"citationCount":108,"citationInfo":2330,"publishDate":2343,"publishYear":2331,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":2344,"openAccess":24,"references":2345,"isForceReanalyzing":409},"867102df-3071-459f-aae7-c558ee7fc4e2","2024-09-02T18:45:31.912+00:00",[],"LIBSVM",{"openalex":2232,"mag":2234,"abstract":2236,"title":2238,"doi":2239},{"VOID":2233},"W2153635508",{"VOID":2235},"2153635508",{"EN":2237},"\u003Cjats:p>LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily apply SVM to their applications. LIBSVM has gained wide popularity in machine learning and many other areas. In this article, we present all implementation details of LIBSVM. Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.\u003C\u002Fjats:p>",{"EN":2230},{"VOID":1778},[141],"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002F10.1145\u002F1961189.1961199",[2243,2260],{"id":2244,"sortIndex":25,"researcher":24,"roles":2245,"affiliations":2246,"properties":2255},"af77a320-6a95-48c1-ac18-3c52542c1c7a",[],[2247],{"id":2248,"sortIndex":25,"affiliation":2249,"properties":24},"0dc86f74-eeac-482b-afe5-643e162cd317",{"id":2248,"createTime":24,"updateTime":24,"relativeEntities":2250,"slug":24,"properties":2251,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2254,"statistic":24},[],{"title":2252},{"VI":2253},"National Taiwan University, Taipei, Taiwan",[],{"title":2256,"openalex":2258},{"EN":2257},"Chih-Chung Chang",{"VOID":2259},"A5103432521",{"id":2261,"sortIndex":105,"researcher":24,"roles":2262,"affiliations":2263,"properties":2270},"37eec33c-e86c-4d72-aa69-8d49adc711fc",[],[2264],{"id":2248,"sortIndex":25,"affiliation":2265,"properties":24},{"id":2248,"createTime":24,"updateTime":24,"relativeEntities":2266,"slug":24,"properties":2267,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2269,"statistic":24},[],{"title":2268},{"VI":2253},[],{"orcid":2271,"title":2273,"openalex":2275},{"VOID":2272},"https:\u002F\u002Forcid.org\u002F0000-0003-4684-8747",{"EN":2274},"Chih‐Jen Lin",{"VOID":2276},"A5068223640",{"url":24,"publisher":2278,"properties":2325},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":2279,"slug":10,"properties":2280,"entityType":22,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":25,"subjectFields":2285,"manageAffiliations":2294,"indexDatabases":2305,"url":90,"thumbnailPath":24,"statistic":2320,"gsStatistic":24,"type":24,"analyzePriority":24},[],{"country":2281,"eissn":2282,"issn":2283,"title":2284},{"VOID":13},{"VOID":15},{"VOID":17},{"EN":19},[2286,2290],{"id":28,"createTime":24,"updateTime":24,"relativeEntities":2287,"label":2288,"description":2289,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":31},{},{"id":34,"createTime":24,"updateTime":24,"relativeEntities":2291,"label":2292,"description":2293,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":37},{},[2295,2300],{"id":41,"createTime":24,"updateTime":24,"relativeEntities":2296,"slug":24,"properties":2297,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2299,"statistic":24},[],{"title":2298},{"EN":45},[],{"id":48,"createTime":24,"updateTime":24,"relativeEntities":2301,"slug":24,"properties":2302,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2304,"statistic":24},[],{"title":2303},{"EN":52},[],[2306,2313],{"id":56,"indexDatabase":2307,"url":69,"indexYears":24,"academicFieldIds":2312,"indexDatabaseRanking":24},{"id":58,"createTime":24,"updateTime":24,"relativeEntities":2308,"label":2309,"description":2310,"key":65,"publicationTags":2311,"standard":24},[],{"EN":61,"VI":61},{"EN":63,"VI":64},[67,68],[71],{"id":73,"indexDatabase":2314,"url":84,"indexYears":85,"academicFieldIds":2319,"indexDatabaseRanking":89},{"id":75,"createTime":24,"updateTime":24,"relativeEntities":2315,"label":2316,"description":2317,"key":81,"publicationTags":2318,"standard":24},[],{"EN":78,"VI":78},{"EN":78,"VI":80},[83],[87,88],{"impactFactor":25,"impactFactorByYear":2321,"i10Index":101,"i10IndexLast5Year":102,"totalPublication":103,"totalPublicationByYear":2322,"totalCitation":106,"totalCitationByYear":2323,"totalCitationPerPublication":112,"totalCitationPerPublicationByYear":2324,"hindexLast5Year":101,"hindex":101},{"2012":93,"2013":94,"2016":95,"2017":96,"2020":97,"2021":98,"2022":99,"2023":100},{"2011":105,"2015":102,"2019":105,"2021":105},{"2011":108,"2015":109,"2019":110,"2021":111},{"2011":108,"2015":114,"2019":110,"2021":111},{"issue":2326,"pages":2327,"volume":2328},{"VOID":567},{"VOID":2101},{"VOID":2329},"2",{"total":108,"publishYear":2331,"statisticByYear":2332},2011,{"2012":93,"2013":94,"2014":2333,"2015":2334,"2016":2335,"2017":2336,"2018":2336,"2019":2337,"2020":2338,"2021":2339,"2022":2340,"2023":2341,"2024":2342},2518,2760,2623,2387,2102,1957,1820,1474,1172,493,"2011-04-01",[67,89],[2346,2349,2352,2355,2358,2361,2364,2367,2370,2373,2376,2379,2382,2385,2388,2391,2394,2397,2400,2403,2406,2409,2412,2415,2418,2421,2424,2427,2430,2433,2436,2439,2442,2445,2448,2451,2454],{"id":24,"text":2347,"url":24,"identifiers":2348},"10.1145\u002F130385.130401",{"doi":2347},{"id":24,"text":2350,"url":24,"identifiers":2351},"10.1162\u002F089976601750399335",{"doi":2350},{"id":24,"text":2353,"url":24,"identifiers":2354},"10.1162\u002F089976602760128081",{"doi":2353},{"id":24,"text":2356,"url":24,"identifiers":2357},"10.1109\u002FTNN.2006.875973",{"doi":2356},{"id":24,"text":2359,"url":24,"identifiers":2360},"10.1002\u002Fasmb.v21:2",{"doi":2359},{"id":24,"text":2362,"url":24,"identifiers":2363},"10.1023\u002FA:1022627411411",{"doi":2362},{"id":24,"text":2365,"url":24,"identifiers":2366},"Crisp D. J. and Burges C. J. C. 2000. A geometric interpretation of ν-SVM classifiers. In Advances in Neural Information Processing Systems S. Solla T. Leen and K.-R. Müller Eds. Vol. 12 MIT Press Cambridge MA.  Crisp D. J. and Burges C. J. C. 2000. A geometric interpretation of ν-SVM classifiers. In Advances in Neural Information Processing Systems S. Solla T. Leen and K.-R. Müller Eds. Vol. 12 MIT Press Cambridge MA.",{},{"id":24,"text":2368,"url":24,"identifiers":2369},"10.1093\u002Fbioinformatics\u002Fbtq463",{"doi":2368},{"id":24,"text":2371,"url":24,"identifiers":2372},"10.5555\u002F1046920.1194907",{"doi":2371},{"id":24,"text":2374,"url":24,"identifiers":2375},"Fine S., 2001, Efficient svm training using low-rank kernel representations, J. Mach. Learn. Res., 2, 243",{},{"id":24,"text":2377,"url":24,"identifiers":2378},"10.5555\u002F1248547.1248600",{"doi":2377},{"id":24,"text":2380,"url":24,"identifiers":2381},"10.1109\u002FICCV.2005.239",{"doi":2380},{"id":24,"text":2383,"url":24,"identifiers":2384},"10.1007\u002Fs12021-008-9041-y",{"doi":2383},{"id":24,"text":2386,"url":24,"identifiers":2387},"Hsu C.-W. Chang C.-C. and Lin C.-J. 2003. A practical guide to support vector classification. Tech. rep. Department of Computer Science National Taiwan University.  Hsu C.-W. Chang C.-C. and Lin C.-J. 2003. A practical guide to support vector classification. Tech. rep. Department of Computer Science National Taiwan University.",{},{"id":24,"text":2389,"url":24,"identifiers":2390},"10.1109\u002F72.991427",{"doi":2389},{"id":24,"text":2392,"url":24,"identifiers":2393},"10.1023\u002FA:1012427100071",{"doi":2392},{"id":24,"text":2395,"url":24,"identifiers":2396},"Joachims T., Advances in Kernel Methods -- Support Vector Learning, B. Schölkopf",{},{"id":24,"text":2398,"url":24,"identifiers":2399},"10.5555\u002F1248547.1248602",{"doi":2398},{"id":24,"text":2401,"url":24,"identifiers":2402},"10.1162\u002F089976601300014493",{"doi":2401},{"id":24,"text":2404,"url":24,"identifiers":2405},"Knerr S., 1990, Neurocomputing: Algorithms, Architectures and Applications",{},{"id":24,"text":2407,"url":24,"identifiers":2408},"Kressel U. H.-G., Advances in Kernel Methods -- Support Vector Learning, B. Schölkopf",{},{"id":24,"text":2410,"url":24,"identifiers":2411},"Lee Y.-J., Proceedings of the 1st SIAM International Conference on Data Mining.",{},{"id":24,"text":2413,"url":24,"identifiers":2414},"Lin C.-J. and Weng R. C. 2004. Simple probabilistic predictions for support vector regression. Tech. rep. Department of Computer Science National Taiwan University.  Lin C.-J. and Weng R. C. 2004. Simple probabilistic predictions for support vector regression. Tech. rep. Department of Computer Science National Taiwan University.",{},{"id":24,"text":2416,"url":24,"identifiers":2417},"10.1007\u002Fs10994-007-5018-6",{"doi":2416},{"id":24,"text":2419,"url":24,"identifiers":2420},"List N., 2007, General polynomial time decomposition algorithms, J. Mach. Learn. Res., 8, 303",{},{"id":24,"text":2422,"url":24,"identifiers":2423},"List N., Proceedings of the 22nd Annual Conference on Computational Learning Theory.",{},{"id":24,"text":2425,"url":24,"identifiers":2426},"10.1017\u002FS1351324906004505",{"doi":2425},{"id":24,"text":2428,"url":24,"identifiers":2429},"Osuna E. Freund R. and Girosi F. 1997a. Support vector machines: Training and applications. AI Memo 1602 Massachusetts Institute of Technology.   Osuna E. Freund R. and Girosi F. 1997a. Support vector machines: Training and applications. AI Memo 1602 Massachusetts Institute of Technology.",{},{"id":24,"text":2431,"url":24,"identifiers":2432},"Osuna E., Proceedings of CVPR'97",{},{"id":24,"text":2434,"url":24,"identifiers":2435},"10.1080\u002F10556780512331318209",{"doi":2434},{"id":24,"text":2437,"url":24,"identifiers":2438},"Platt J. C., Advances in Kernel Methods - Support Vector Learning, B. Schölkopf",{},{"id":24,"text":2440,"url":24,"identifiers":2441},"Platt J. C., Advances in Large Margin Classifiers, A. Smola, P. Bartlett, B. Schölkopf, and D",{},{"id":24,"text":2443,"url":24,"identifiers":2444},"10.1162\u002F089976601750264965",{"doi":2443},{"id":24,"text":2446,"url":24,"identifiers":2447},"10.1162\u002F089976600300015565",{"doi":2446},{"id":24,"text":2449,"url":24,"identifiers":2450},"10.5555\u002F1756006.1859915",{"doi":2449},{"id":24,"text":2452,"url":24,"identifiers":2453},"Vapnik V. 1998. Statistical Learning Theory. Wiley New York.  Vapnik V. 1998. Statistical Learning Theory. Wiley New York.",{},{"id":24,"text":2455,"url":24,"identifiers":2456},"10.5555\u002F1005332.1016791",{"doi":2455},{"id":2458,"createTime":2459,"updateTime":2459,"relativeEntities":2460,"slug":2461,"properties":2462,"entityType":136,"verifyStatus":137,"verifyTime":2472,"verifyNote":139,"languages":2473,"translateLanguages":24,"viewCount":25,"primaryUrl":2474,"fullTextUrl":24,"authors":2475,"publicationType":225,"publisherRelationship":2585,"citationCount":110,"citationInfo":2639,"publishDate":2643,"publishYear":2640,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":2644,"openAccess":24,"references":2645,"isForceReanalyzing":409},"9633f62b-4572-4e85-a615-202fbb18ac9c","2024-08-31T23:20:42.574+00:00",[],"BAMB",{"openalex":2463,"mag":2465,"abstract":2467,"title":2469,"doi":2470},{"VOID":2464},"W2980507899",{"VOID":2466},"2980507899",{"EN":2468},"\u003Cjats:p>The discovery of Markov blanket (MB) for feature selection has attracted much attention in recent years, since the MB of the class attribute is the optimal feature subset for feature selection. However, almost all existing MB discovery algorithms focus on either improving computational efficiency or boosting learning accuracy, instead of both. In this article, we propose a novel MB discovery algorithm for balancing efficiency and accuracy, called <underline>BA<\u002Funderline>lanced <underline>M<\u002Funderline>arkov <underline>B<\u002Funderline>lanket (BAMB) discovery. To achieve this goal, given a class attribute of interest, BAMB finds candidate PC (parents and children) and spouses and removes false positives from the candidate MB set in one go. Specifically, once a feature is successfully added to the current PC set, BAMB finds the spouses with regard to this feature, then uses the updated PC and the spouse set to remove false positives from the current MB set. This makes the PC and spouses of the target as small as possible and thus achieves a trade-off between computational efficiency and learning accuracy. In the experiments, we first compare BAMB with 8 state-of-the-art MB discovery algorithms on 7 benchmark Bayesian networks, then we use 10 real-world datasets and compare BAMB with 12 feature selection algorithms, including 8 state-of-the-art MB discovery algorithms and 4 other well-established feature selection methods. On prediction accuracy, BAMB outperforms 12 feature selection algorithms compared. On computational efficiency, BAMB is close to the IAMB algorithm while it is much faster than the remaining seven MB discovery algorithms.\u003C\u002Fjats:p>",{"EN":2461},{"VOID":2471},"10.1145\u002F3335676","2024-08-31T23:20:42.573+00:00",[141],"https:\u002F\u002Fdl.acm.org\u002Fdoi\u002F10.1145\u002F3335676",[2476,2495,2512,2528,2547,2566],{"id":2477,"sortIndex":25,"researcher":24,"roles":2478,"affiliations":2479,"properties":2488},"dc72c562-2f19-4e25-b363-aab4537d20af",[],[2480],{"id":2481,"sortIndex":25,"affiliation":2482,"properties":24},"1a5066c9-a9fa-4c5d-87f3-a8879d2b50fe",{"id":2481,"createTime":24,"updateTime":24,"relativeEntities":2483,"slug":24,"properties":2484,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2487,"statistic":24},[],{"title":2485},{"VI":2486},"Hefei University of Technology, Hefei, Anhui, China",[],{"orcid":2489,"title":2491,"openalex":2493},{"VOID":2490},"https:\u002F\u002Forcid.org\u002F0000-0002-6423-0783",{"EN":2492},"Hao Wang",{"VOID":2494},"A5100618082",{"id":2496,"sortIndex":105,"researcher":24,"roles":2497,"affiliations":2498,"properties":2505},"44824448-c5a0-4bc8-813c-eeb79342b525",[],[2499],{"id":2481,"sortIndex":25,"affiliation":2500,"properties":24},{"id":2481,"createTime":24,"updateTime":24,"relativeEntities":2501,"slug":24,"properties":2502,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2504,"statistic":24},[],{"title":2503},{"VI":2486},[],{"orcid":2506,"title":2508,"openalex":2510},{"VOID":2507},"https:\u002F\u002Forcid.org\u002F0000-0003-2442-4572",{"EN":2509},"Kui Yu",{"VOID":2511},"A5100719462",{"id":2513,"sortIndex":102,"researcher":24,"roles":2514,"affiliations":2515,"properties":2522},"be09de1b-7bf2-43ea-b261-6307a41d4a7d",[],[2516],{"id":2481,"sortIndex":25,"affiliation":2517,"properties":24},{"id":2481,"createTime":24,"updateTime":24,"relativeEntities":2518,"slug":24,"properties":2519,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2521,"statistic":24},[],{"title":2520},{"VI":2486},[],{"orcid":2523,"title":2525,"openalex":2526},{"VOID":2524},"https:\u002F\u002Forcid.org\u002F0000-0002-5963-6252",{"EN":2492},{"VOID":2527},"A5100618081",{"id":2529,"sortIndex":205,"researcher":24,"roles":2530,"affiliations":2531,"properties":2540},"16fe974c-7319-4fe8-b06e-dce3c7d96b5e",[],[2532],{"id":2533,"sortIndex":25,"affiliation":2534,"properties":24},"11d9cff8-703e-4b89-abf5-3772f0c488c9",{"id":2533,"createTime":24,"updateTime":24,"relativeEntities":2535,"slug":24,"properties":2536,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2539,"statistic":24},[],{"title":2537},{"VI":2538},"University of South Australia, Adelaide, SA, Australia",[],{"orcid":2541,"title":2543,"openalex":2545},{"VOID":2542},"https:\u002F\u002Forcid.org\u002F0000-0003-2843-5738",{"EN":2544},"Lin Liu",{"VOID":2546},"A5100383342",{"id":2548,"sortIndex":97,"researcher":24,"roles":2549,"affiliations":2550,"properties":2559},"35c39fc1-7d70-4bd8-8279-2c486e454d94",[],[2551],{"id":2552,"sortIndex":25,"affiliation":2553,"properties":24},"8a23e817-a2f0-458e-aac5-231baaea9d75",{"id":2552,"createTime":24,"updateTime":24,"relativeEntities":2554,"slug":24,"properties":2555,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2558,"statistic":24},[],{"title":2556},{"EN":2557},"University of Massachusetts Boston, Boston, MA, USA",[],{"orcid":2560,"title":2562,"openalex":2564},{"VOID":2561},"https:\u002F\u002Forcid.org\u002F0000-0002-3383-551X",{"EN":2563},"Wei Ding",{"VOID":2565},"A5088432110",{"id":2567,"sortIndex":101,"researcher":24,"roles":2568,"affiliations":2569,"properties":2578},"8e5b7553-279e-466f-803f-bb8af9c6034b",[],[2570],{"id":2571,"sortIndex":25,"affiliation":2572,"properties":24},"75414344-86a8-47be-89c9-c64263db782e",{"id":2571,"createTime":24,"updateTime":24,"relativeEntities":2573,"slug":24,"properties":2574,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2577,"statistic":24},[],{"title":2575},{"EN":2576},"Mininglamp Technology, Beijing, China",[],{"orcid":2579,"title":2581,"openalex":2583},{"VOID":2580},"https:\u002F\u002Forcid.org\u002F0000-0003-2396-1704",{"EN":2582},"Xindong Wu",{"VOID":2584},"A5080738591",{"url":24,"publisher":2586,"properties":2633},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":2587,"slug":10,"properties":2588,"entityType":22,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":25,"subjectFields":2593,"manageAffiliations":2602,"indexDatabases":2613,"url":90,"thumbnailPath":24,"statistic":2628,"gsStatistic":24,"type":24,"analyzePriority":24},[],{"country":2589,"eissn":2590,"issn":2591,"title":2592},{"VOID":13},{"VOID":15},{"VOID":17},{"EN":19},[2594,2598],{"id":28,"createTime":24,"updateTime":24,"relativeEntities":2595,"label":2596,"description":2597,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":31},{},{"id":34,"createTime":24,"updateTime":24,"relativeEntities":2599,"label":2600,"description":2601,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":37},{},[2603,2608],{"id":41,"createTime":24,"updateTime":24,"relativeEntities":2604,"slug":24,"properties":2605,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2607,"statistic":24},[],{"title":2606},{"EN":45},[],{"id":48,"createTime":24,"updateTime":24,"relativeEntities":2609,"slug":24,"properties":2610,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2612,"statistic":24},[],{"title":2611},{"EN":52},[],[2614,2621],{"id":56,"indexDatabase":2615,"url":69,"indexYears":24,"academicFieldIds":2620,"indexDatabaseRanking":24},{"id":58,"createTime":24,"updateTime":24,"relativeEntities":2616,"label":2617,"description":2618,"key":65,"publicationTags":2619,"standard":24},[],{"EN":61,"VI":61},{"EN":63,"VI":64},[67,68],[71],{"id":73,"indexDatabase":2622,"url":84,"indexYears":85,"academicFieldIds":2627,"indexDatabaseRanking":89},{"id":75,"createTime":24,"updateTime":24,"relativeEntities":2623,"label":2624,"description":2625,"key":81,"publicationTags":2626,"standard":24},[],{"EN":78,"VI":78},{"EN":78,"VI":80},[83],[87,88],{"impactFactor":25,"impactFactorByYear":2629,"i10Index":101,"i10IndexLast5Year":102,"totalPublication":103,"totalPublicationByYear":2630,"totalCitation":106,"totalCitationByYear":2631,"totalCitationPerPublication":112,"totalCitationPerPublicationByYear":2632,"hindexLast5Year":101,"hindex":101},{"2012":93,"2013":94,"2016":95,"2017":96,"2020":97,"2021":98,"2022":99,"2023":100},{"2011":105,"2015":102,"2019":105,"2021":105},{"2011":108,"2015":109,"2019":110,"2021":111},{"2011":108,"2015":114,"2019":110,"2021":111},{"issue":2634,"pages":2635,"volume":2637},{"VOID":571},{"VOID":2636},"1-25",{"VOID":2638},"10",{"total":110,"publishYear":2640,"statisticByYear":2641},2019,{"2019":105,"2020":97,"2021":98,"2022":816,"2023":2642,"2024":101},12,"2019-09-30",[67,89],[2646,2649,2652,2655,2658,2661,2664,2666,2669,2672,2675,2678,2681,2684,2687,2690,2693,2697,2700,2703,2706,2709,2712,2715,2718,2721,2724,2727,2730,2733,2736,2739,2742],{"id":24,"text":2647,"url":24,"identifiers":2648},"Aliferis Constantin F., 2010, Koutsoukos",{},{"id":24,"text":2650,"url":24,"identifiers":2651},"Aliferis Constantin F., 2003, Proceedings of the AMIA Annual Symposium Proceedings. American Medical Informatics Association, 21",{},{"id":24,"text":2653,"url":24,"identifiers":2654},"Beinlich Ingo A., Proceedings of the Conference on Artificial Intelligence in Medicine (AIME’89)",{},{"id":24,"text":2656,"url":24,"identifiers":2657},"10.1023\u002FA:1007421730016",{"doi":2656},{"id":24,"text":2659,"url":24,"identifiers":2660},"10.1007\u002Fs10115-017-1140-3",{"doi":2659},{"id":24,"text":2662,"url":24,"identifiers":2663},"10.1016\u002Fj.patcog.2010.10.023",{"doi":2662},{"id":24,"text":1778,"url":24,"identifiers":2665},{"doi":1778},{"id":24,"text":2667,"url":24,"identifiers":2668},"10.1109\u002FTPAMI.2010.195",{"doi":2667},{"id":24,"text":2670,"url":24,"identifiers":2671},"A. P. Dawid R. G. Cowell S. L. Lauritzen and D. J. Spiegelhalter. 1999. Probabilistic Networks and Expert Systems. Springer-Verlag.  A. P. Dawid R. G. Cowell S. L. Lauritzen and D. J. Spiegelhalter. 1999. Probabilistic Networks and Expert Systems. Springer-Verlag.",{},{"id":24,"text":2673,"url":24,"identifiers":2674},"Dua Dheeru and Efi Karra Taniskidou. 2017. UCI Machine Learning Repository. Retrieved from http:\u002F\u002Farchive.ics.uci.edu\u002Fml.  Dua Dheeru and Efi Karra Taniskidou. 2017. UCI Machine Learning Repository. Retrieved from http:\u002F\u002Farchive.ics.uci.edu\u002Fml.",{},{"id":24,"text":2676,"url":24,"identifiers":2677},"Fu Shunkai, 2008, Desmarais",{},{"id":24,"text":2679,"url":24,"identifiers":2680},"10.1109\u002FTCYB.2016.2539338",{"doi":2679},{"id":24,"text":2682,"url":24,"identifiers":2683},"10.1016\u002Fj.ijar.2016.09.009",{"doi":2682},{"id":24,"text":2685,"url":24,"identifiers":2686},"Hitt Ben, 2006, Multiple high-resolution serum proteomic features for ovarian cancer detection, U.S. Patent App., 11, 018",{},{"id":24,"text":2688,"url":24,"identifiers":2689},"Margaritis Dimitris, Advances in Neural Information Processing Systems",{},{"id":24,"text":2691,"url":24,"identifiers":2692},"Niinimki T., 2012, Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI’12)",{},{"id":24,"text":2694,"url":24,"identifiers":2695},"Judea Pearl. 1988. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann series in representation and reasoning.  Judea Pearl. 1988. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann series in representation and reasoning.",{"doi":2696},"10.1016\u002FB978-0-08-051489-5.50008-4",{"id":24,"text":2698,"url":24,"identifiers":2699},"Pearl Judea, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference",{},{"id":24,"text":2701,"url":24,"identifiers":2702},"10.1016\u002Fj.ijar.2006.06.008",{"doi":2701},{"id":24,"text":2704,"url":24,"identifiers":2705},"10.1109\u002FTPAMI.2005.159",{"doi":2704},{"id":24,"text":2707,"url":24,"identifiers":2708},"Silander Tomi, 2006, Proceedings of the 22nd Annual Conference on Uncertainty in Artificial Intelligence (UAI’06)",{},{"id":24,"text":2710,"url":24,"identifiers":2711},"Spirtes Peter, Prediction, and Search",{},{"id":24,"text":2713,"url":24,"identifiers":2714},"Statnikov A., 2003, Technical Report DSL-03-01",{},{"id":24,"text":2716,"url":24,"identifiers":2717},"10.1145\u002F956750.956838",{"doi":2716},{"id":24,"text":2719,"url":24,"identifiers":2720},"Tsamardinos Ioannis, 2003, Proceedings of the International Conference of the Florida Artificial Intelligence Research Society (FLAIRS’03), 2",{},{"id":24,"text":2722,"url":24,"identifiers":2723},"10.1007\u002Fs10994-006-6889-7",{"doi":2722},{"id":24,"text":2725,"url":24,"identifiers":2726},"10.1007\u002Fs10115-017-1131-4",{"doi":2725},{"id":24,"text":2728,"url":24,"identifiers":2729},"10.1109\u002FICDM.2005.134",{"doi":2728},{"id":24,"text":2731,"url":24,"identifiers":2732},"Yu Kui, 2018, A unified view of causal and non-causal feature selection, Arxiv Preprint Arxiv, 1802, 05844",{},{"id":24,"text":2734,"url":24,"identifiers":2735},"Yu Kui, 2019, Multi-source causal feature selection, IEEE Trans. Pattern Anal. Mach. Intell. DOI, 10",{},{"id":24,"text":2737,"url":24,"identifiers":2738},"10.1145\u002F2976744",{"doi":2737},{"id":24,"text":2740,"url":24,"identifiers":2741},"Yu Lei, 2004, Efficient feature selection via analysis of relevance and redundancy, J. Mach. Learn. Res. 5",{},{"id":24,"text":2743,"url":24,"identifiers":2744},"10.1109\u002FTKDE.2011.222",{"doi":2743}]