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The problem becomes more challenging for research articles. Over the years, many datasets and techniques have been developed to attempt automatic novelty detection. However, the majority of the existing textual novelty detection investigations are targeted toward general domains like newswire. A comprehensive dataset for scientific novelty detection is not available in the literature. In this paper, we present a new triplet-based corpus (SciND) for scientific novelty detection from research articles via knowledge graphs. The proposed dataset consists of three types of triples (i) triplet for the knowledge graph, (ii) novel triplets, and (iii) non-novel triplets. We build a scientific knowledge graph for research articles using triplets across several natural language processing (NLP) domains and extract novel triplets from the paper published in the year 2021. For the non-novel articles, we use blog post summaries of the research articles. Our knowledge graph is domain-specific. We build the knowledge graph for seven NLP domains. We further use a feature-based novelty detection scheme from the research articles as a baseline. Moreover, we show the applicability of our proposed dataset using our baseline novelty detection algorithm. Our algorithm yields a baseline F1 score of 72%. We show analysis and discuss the future scope using our proposed dataset. To the best of our knowledge, this is the very first dataset for scientific novelty detection via a knowledge graph. We make our codes and dataset publicly available at \n              https:\u002F\u002Fgithub.com\u002F92Komal\u002FScientific_Novelty_Detection\n              \n            .",{"EN":112},"SciND: a new triplet-based dataset for scientific novelty detection via knowledge graphs",{"VOID":114},"[\"15667760482681989595\"]",{"VOID":116},"(2023) Bert. https:\u002F\u002Fhuggingface.co\u002Fdocs\u002Ftransformers\u002Fmodel_doc\u002Fbert\n(2023) CNN vs. RNN: How are they different? https:\u002F\u002Fwww.techtarget.com\u002Fsearchenterpriseai\u002Ffeature\u002FCNN-vs-RNN-How-they-differ-and-where-they-overlap\n(2023) Day 192: NLP papers summary—guiding extractive summarization with question-answering rewards-ryan ong. https:\u002F\u002Fryanong.co.uk\u002F\n(2023) Difference between article and blog—geeksforgeeks. https:\u002F\u002Fwww.geeksforgeeks.org\u002Fdifference-between-article-and-blog\u002F\n(2023) Medium—where good ideas find you. https:\u002F\u002Fmedium.com\u002F\n(2023) Memory networks the morning paper. https:\u002F\u002Fblog.acolyer.org\u002F\n(2023) On learning language-invariant representations for universal machine translation—machine learning blog ml@cmu carnegie mellon university. https:\u002F\u002Fblog.ml.cmu.edu\u002F\n(2023) Papers i read . notes and summaries. https:\u002F\u002Fshagunsodhani.com\u002Fpapers-I-read\u002F\n(2023) papers\u002Fneural-nets at master. aleju\u002Fpapers. github. https:\u002F\u002Fgithub.com\u002Faleju\u002Fpapers\u002Ftree\u002Fmaster\u002Fneural-nets\n(2023) Sik-ho tsang-medium. https:\u002F\u002Fsh-tsang.medium.com\u002F\n(2023) Taming recurrent neural networks for better summarization abigail see. http:\u002F\u002Fwww.abigailsee.com\u002F\n(2023) Towards a conversational agent that can chat about...anything—google ai blog. https:\u002F\u002Fai.googleblog.com\u002F2020\u002F01\u002Ftowards-conversational-agent-that-can.html\n(2023) Towards data science. https:\u002F\u002Ftowardsdatascience.com\u002F\n(2023) What makes a good conversation? abigail see. http:\u002F\u002Fwww.abigailsee.com\n(2023) Write and structure a journal article well writing your paper. https:\u002F\u002Fauthorservices.taylorandfrancis.com\nAl-Zaidy, R.A., Caragea, C., Giles, C.L.: BI-LSTM-CRF sequence labeling for keyphrase extraction from scholarly documents. 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Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, ACL 2020, Online, July 5–10, 2020, pp. 101–108. Association for Computational Linguistics (2020) https:\u002F\u002Fdoi.org\u002F10.18653\u002FV1\u002F2020.ACL-DEMOS.14\nRuder, S.: An overview of multi-task learning in deep neural networks. CoRR (2017). arXiv:1706.05098\nSaikh, T., Ghosal, T., Ekbal, A., et al.: Document level novelty detection: Textual entailment lends a helping hand. In: Bandyopadhyay, S. (ed.) Proceedings of the 14th International Conference on Natural Language Processing, ICON 2017, Kolkata, India, December 18–21, 2017, pp. 131–140. NLP Association of India (2017). https:\u002F\u002Faclanthology.org\u002FW17-7517\u002F\nShailabh, S., Chaurasia, S., Modi, A.: Knowgraph@iitk at semeval-2021 task 11: Building knowledgegraph for NLP research. CoRR (2021) arXiv:2104.01619\nSoboroff, I., Harman, D.: Overview of the TREC 2003 novelty track. In: Voorhees, E.M., Buckland, L.P. (eds.) Proceedings of The Twelfth Text REtrieval Conference, TREC 2003, Gaithersburg, Maryland, USA, November 18–21, 2003, NIST Special Publication, vol 500-255. National Institute of Standards and Technology (NIST), pp. 38–53 (2003). http:\u002F\u002Ftrec.nist.gov\u002Fpubs\u002Ftrec12\u002Fpapers\u002FNOVELTY.OVERVIEW.pdf\nSoboroff, I., Harman, D.: Novelty detection: The TREC experience. In: HLT\u002FEMNLP 2005, Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference, 6–8 October 2005, Vancouver, British Columbia, Canada, pp. 105–112. The Association for Computational Linguistics (2005) https:\u002F\u002Faclanthology.org\u002FH05-1014\u002F\nSouza, F., Nogueira, RF., de Alencar Lotufo, R.: Portuguese named entity recognition using BERT-CRF. CoRR (2019) arXiv:1909.10649\nSpeer, R., Chin, J., Havasi, C.: Conceptnet 5.5: An open multilingual graph of general knowledge. 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CLIR (2002) http:\u002F\u002Fwww.clir.org\u002Fpubs\u002Freports\u002Fpub105\u002Fpub105.pdf",{},{"id":18,"text":809,"url":18,"identifiers":810},"Borgman, C.L.: Social Aspects of Digital Libraries-Final Report to the NSF. Technical report (1996) http:\u002F\u002Fis.gseis.ucla.edu\u002Fresearch\u002Fdl\u002FUCLA_DL_Report.html",{"doi":811},"10.1145\u002F226931.226964",{"id":18,"text":813,"url":18,"identifiers":814},"Kovács, L., Micsik, A.: The evaluation computer: a model for structuring evaluation activities. In: Agosti, M., Fuhr, N. (eds.) DELOS Workshop on the Evaluation of Digital Libraries, Padova, Italy (2004) http:\u002F\u002Fdlib.ionio.gr\u002Fwp7\u002F workshop2004_program.html",{},{"id":18,"text":816,"url":18,"identifiers":817},"Banwell, L., Coulson, G.: Users and user study methodology: the JUBILEE project. Inf. Res. 9, 47–56 (2004) http:\u002F\u002F informationr.net\u002Fir\u002F9-2\u002Fpaper167.html",{},{"id":18,"text":819,"url":18,"identifiers":820},"Jeng J. (2005). What is usability in the context of the digital library and how can it be measured? Inf. Technol. Libr. 24: 47–56",{},{"id":18,"text":822,"url":18,"identifiers":823},"Xie H. (2006). Evaluation of digital libraries: criteria and problems from users perspectives. Libr. Inf. Res. 28: 433–452",{"doi":824},"10.1016\u002Fj.lisr.2006.06.002",{"id":18,"text":826,"url":18,"identifiers":827},"Klas, C., Albrechtsen, H.N.F., Hansen, P., Kapidakis, S., Kovacs, L., Kriewel, S., Micsik, A., Papatheodorou, C., Tsakonas, G., Jacob, E.: A logging scheme for comparative digital library evaluation. In: Lecture Notes In Computer Science, vol. 4172, pp. 267—278 Springer, Berlin (2006) Research and Advanced Technology for Digital Libraries: 10th European Conference, ECDL 2006, Alicante, Spain, September 17—22, 2006. 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This paper is focused on automatic citation analysis and summarization for the scientific literature of computational linguistics, which are also the shared tasks in the 2016 workshop of the 2nd Computational Linguistics Scientific Document Summarization at BIRNDL 2016 (The Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries). Each citation linkage between a citation and the spans of text in the reference paper is recognized according to their content similarities via various computational methods. Then the cited text span is classified to five pre-defined facets, i.e., Hypothesis, Implication, Aim, Results and Method, based on various features of lexicons and rules via Support Vector Machine and Voting Method. Finally, a summary of the reference paper from the cited text spans is generated within 250 words. hLDA (hierarchical Latent Dirichlet Allocation) topic model is adopted for content modeling, which provides knowledge about sentence clustering (subtopic) and word distributions (abstractiveness) for summarization. We combine hLDA knowledge with several other classical features using different weights and proportions to evaluate the sentences in the reference paper. Our systems have been ranked top one and top two according to the evaluation results published by BIRNDL 2016, which has verified the effectiveness of our methods.",{"EN":957},"Computational linguistics literature and citations oriented citation linkage, classification and summarization",{"VOID":959},"[]",{"VOID":961},"Wan, X., Yang, J., Xiao, J.: Using cross-document random walks for topic-focused multi-document. In: IEEE\u002FWic\u002FACM International Conference on Web Intelligence, pp. 1012–1018 (2006)\nGarca, J., Laurent, F., Gillard, O.F.: Bag-of-senses versus bag-of-words: comparing semantic and lexical approaches on sentence extraction. In: TAC 2008 Workshop—Notebook Papers and Results (2008)\nBellemare, S., Bergler, S., Witte, R.: ERSS at TAC 2008. In: TAC 2008 Proceedings (2008)\nConroy, J., Schlesinger, J.D.: CLASSY at TAC 2008 Metrics. In: TAC 2008 Proceedings (2008)\nZheng, Y., Takenobu, T.: The TITech Summarization System at TAC-2009. In: TAC 2009 Proceedings (2009)\nAnnie, L., Ani, N.: Predicting summary quality using limited human input. In: TAC 2009 Proceedings (2009)\nDarling, W.M.: Multi-document summarization from first principles. In: Proceedings of the third Text Analysis Conference, TAC-2010. NIST, vol. 150 (2010)\nKokil, J., Muthu, K.C., Sajal, R., MinYen, K.: Overview of the 2nd computational linguistics scientific document summarization shared task (CL-SciSumm 2016). In: The Proceedings of the Joint Workshop on Bibliometric-Enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2016), Newark, New Jersey, USA (2016)\nGenest, P., Lapalme, G., Qubec, M.: Text generation for abstractive summarization. In: TAC 2010 Proceedings (2010)\nJin, F., Huang, M., Zhu, X.: The THU summarization systems at TAC 2010. In: Text Analysis Conference (2010)\nZhang, R., Ouyang, Y., Li, W., Zhang, R., Ouyang, Y., Li, W.: Guided summarization with aspect recognition. In: TAC 2011 Proceedings (2011)\nMarina, L., Natalia, V.: Multilingual multi-document summarization with POLY. In: Proceedings of the MultiLing 2013 Workshop on Multilingual Multi-document Summarization (2013)\nSteinberger, J.: The UWB summariser at multiling-2013. In: Proceedings of the MultiLing 2013 Workshop on Multilingual Multi-document Summarization (2013)\nArdjomand, N., Mcalister, J.C., Rogers, N.J., Tan, P.H., George, A.J., Larkin, D. F.: Multilingual summarization: dimensionality reduction and a step towards optimal term coverage. In: Multiling 2013 Workshop on Multilingual Multi-Document Summarization, pp. 3899–3905 (2013)\nAnechitei, D.A., Ignat, E.: Multi-lingual summarization system based on analyzing the discourse structure at MultiLing 2013. In: Proceedings of the MultiLing 2013 Workshop on Multilingual Multi-document Summarization (2013)\nEl-Haj, M., Rayson, P.: Using a keyness metric for single and multi document summarisation. In: Multiling 2013 Workshop, ACL (2013)\nFattah, M.A.: A hybrid machine learning model for multi-document summarization. Appl. Intell. 40(40), 592–600 (2014)\nZhang, R., Li, W., Gao, D., Ouyang, Y.: Automatic twitter topic summarization with speech acts. IEEE Trans. Audio Speech Lang. Process. 21(3), 649–658 (2013)\nXu, Y.D., Zhang, X.D., Quan, G.R., Wang, Y.D.: MRS for multi-document summarization by sentence extraction. Tele-commun. Syst. 53(1), 91–98 (2013)\nArora, R., Ravindran, B.: Latent dirichlet allocation based multi-document summarization. In: The Workshop on Analytics for Noisy Unstructured Text Data. ACM, pp. 91–97 (2008)\nKrestel, R., Fankhauser, P., Nejdl, W.: Latent dirichlet allocation for tag recommendation. In: ACM Conference on Recommender Systems, pp. 61–68 (2009)\nGriffiths, T.L., Steyvers, M., Blei, D.M., Tenenbaum, J.B.: Integrating topics and syntax. Adv. Neural Inf. Process. Syst. 17, 537–544 (2010)\nBlei, D.M., Lafferty, J. D.: Dynamic topic models. In: Proceedings of the 23rd International Conference on Machine Learning, pp. 113–120 (2006)\nWang, C., Blei, D.M.: Decoupling sparsity and smoothness in the discrete hierarchical Dirichlet process. Advances in Neural Information Processing Systems 22. In: Conference on Neural Information Processing Systems 2009. Proceedings of A Meeting Held 7–10 December 2009, Vancouver, British Columbia, Canada, pp. 1982–1989 (2009)\nTeh, Y.W., Jordan, M.I., Beal, M.J., Blei, D.M. Sharing clusters among related groups: hierarchical Dirichlet processes. Advanced Neural Inf Process Syst 37(2), 1385–1392 (2004)\nBlei, D.M., Griffiths, T.L., Jordan, M.I.: The nested Chinese restaurant process and bayesian nonparametric inference of topic hierarchies. J. ACM 57(2), 87–103 (2010)\nCelikyilmaz, A., HakkaniTur, D.: A hybrid hierarchical model for multi-document summarization. In: ACL 2010, Proceedings of the, Meeting of the Association for Computational Linguistics, July 11–16, 2010, Uppsala, Sweden, pp. 815–824 (2010)\nRen, Z., De Rijke, M.: Summarizing contrastive themes via hierarchical non-parametric processes. In: International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, pp. 93–102 (2015)\nElkiss, A., Shen, S., Fader, A., Erkan, G., States, D., Radev, D.: Blind men and elephants: what do citation summaries tell us about a research article? J. Am. Soc. Inf. Sci. Technol. 59(1), 51–62 (2008)\nQazvinian, V., Radev, D.R.: Scientific paper summarization using citation summary networks. In: Proceedings of the 22nd International Conference on Computational Linguistics-Volume 1. Association for Computational Linguistics (2008)\nQazvinian, V., Radev, D.R., Özgür, A.: Citation summarization through keyphrase extraction. In: Proceedings of the 23rd International Conference on Computational Linguistics. Association for Computational Linguistics (2010)\nAbu-Jbara, A., Radev, D.: Coherent citation-based summarization of scientific papers. In: Meeting of the Association for Computational Linguistics: Human Language Technologies, Portland, Oregon, pp. 500–509 (2010)\nMikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. Comput. Sci. arXiv:1301.3781 (2013)\nLe, Q.V., Mikolov, T.: Distributed representations of sentences and documents. Comput. Sci. 4, 1188–1196 (2014)\nHeng, W., Yu, J., Li, L., Liu, Y.: Research on key factors in multi-document topic modelling application with HLDA. J. Chin. Inf. Process. 27(6), 117–127 (2013)\nHuang, T., Li, L., Zhang, Y., Chi, J.: Summarization based on multiple feature combination. In: Proceedings of 2016 4th IEEE International Conference on Cloud Computing and Intelligence Systems (IEEE CCIS 2016), 2016.8.17–19, Beijing, China, pp. 11–15 (2016)\nHuang, T., Li, L., Zhang, Y.: Multilingual multi-document summarization with enhanced hLDA features. In: Springer Lecture Notes in Artificial Intelligence, LNAI10035, Subseries of Lecture Notes in Computer Science, Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated BigData, 15th China National Conference, CCL 2016, and 4th International Symposium, NLP-NABD 2016. Yantai, China, October 15–16, 2016, Proceedings, pp. 299–312 (2016)\nCao, Z., Li, W., Wu, D.: PolyU at CL-SciSumm 2016. In: Proceedings of the Joint Workshop on Bibliometric-Enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL2016), Newark, NJ, USA, pp. 132–138, June 2016\nNomoto, T.: NEAL: A neurally enhanced approach to linking citation and reference. In: Proceedings of the Joint Workshop on Bibliometric-Enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL2016), Newark, NJ, USA, pp. 168–174, June 2016\nSaggion, H., AbuRa’Ed, A., Ronzano, F.: Trainable Citation-enhanced summarization of scientific articles. In: Proceedings of the Joint Workshop on Bibliometric-Enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL2016), Newark, NJ, USA, pp. 175–186, June 2016\nConroy, J., Davis, S.: Vector space and language models for scientific document summarization. In: NAACL-HLT. 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Association for Computing Machinery, New York, NY, USA, CIKM ’17, pp. 2375–2378 (2017). https:\u002F\u002Fdoi.org\u002F10.1145\u002F3132847.3133135","https:\u002F\u002Fdoi.org\u002F10.1145\u002F3132847.3133135",{"doi":1550},"10.1145\u002F3132847.3133135",{"id":1552,"createTime":1553,"updateTime":1554,"relativeEntities":1555,"slug":1556,"properties":1557,"entityType":119,"verifyStatus":120,"verifyTime":1566,"verifyNote":122,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":1567,"fullTextUrl":18,"authors":1568,"publicationType":187,"publisherRelationship":1628,"citationCount":1675,"citationInfo":1676,"publishDate":1679,"publishYear":1677,"citationAnalyzeStatus":17,"lastCitationAnalyze":1680,"indexDatabases":1681,"openAccess":18,"references":1682,"isForceReanalyzing":240},"1245bbd0-6335-424d-8071-77cdc86edf2a","2024-02-07T20:48:36.752+00:00","2025-10-27T03:22:02.424+00:00",[],"The-case-for-the-Humanities-Citation-Index-HuCI-a-citation-index-by-the-humanities-for-the-humanities",{"abstract":1558,"title":1560,"gsPaper":1562,"doi":1564},{"EN":1559},"Citation indexes are by now part of the research infrastructure in use by most scientists: a necessary tool in order to cope with the increasing amounts of scientific literature being published. Commercial citation indexes are designed for the sciences and have uneven coverage and unsatisfactory characteristics for humanities scholars, while no comprehensive citation index is published by a public organisation. We argue that an open citation index for the humanities is desirable, for four reasons: it would greatly improve and accelerate the retrieval of sources, it would offer a way to interlink collections across repositories (such as archives and libraries), it would foster the adoption of metadata standards and best practices by all stakeholders (including publishers) and it would contribute research data to fields such as bibliometrics and science studies. We also suggest that the citation index should be informed by a set of requirements relevant to the humanities. We discuss four such requirements: source coverage must be comprehensive, including books and citations to primary sources; there needs to be chronological depth, as scholarship in the humanities remains relevant over time; the index should be collection driven, leveraging the accumulated thematic collections of specialised research libraries; and it should be rich in context in order to allow for the qualification of each citation, for example, by providing citation excerpts. We detail the fit-for-purpose research infrastructure which can make the Humanities Citation Index a reality. Ultimately, we argue that a citation index for the humanities can be created by humanists, via a collaborative, distributed and open effort.",{"EN":1561},"The case for the Humanities Citation Index (HuCI): a citation index by the humanities, for the 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Italy",[],{"id":1599,"sortIndex":83,"affiliation":1600,"properties":18},"9f6db45b-f81b-4cd4-845c-d277e8ec64cf",{"id":1599,"createTime":18,"updateTime":18,"relativeEntities":1601,"slug":18,"properties":1602,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1605,"statistic":18},[],{"title":1603},{"VI":1604},"Digital Humanities Advanced Research Centre (\u002FDH.arc), Department of Classical Philology and Italian Studies, University of Bologna, Bologna, Italy",[],{"title":1607,"gsAuthor":1609},{"VI":1608},"Silvio 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Sci. Data 3, 160018 (2016). https:\u002F\u002Fdoi.org\u002F10.1038\u002Fsdata.2016.18","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fsdata.2016.18",{"mag":2094,"pmc":2095,"openalex":2096,"pm":2097,"doi":2098},"2302501749","4792175","W2302501749","26978244","10.1038\u002Fsdata.2016.18",{"id":18,"text":2100,"url":2101,"identifiers":2102},"Bilder, G., Lin, J., Neylon, C.: The Principles of Open Scholarly Infrastructure (2020). https:\u002F\u002Fdoi.org\u002F10.24343\u002FC34W2H","https:\u002F\u002Fdoi.org\u002F10.24343\u002FC34W2H",{"doi":2103},"10.24343\u002FC34W2H",{"id":1424,"text":2105,"url":1426,"identifiers":2106},"COAR WG Next Generation Repositories: Behaviours and Technical Recommendations of the COAR Next Generation Repositories Working Group. Recommendation, COAR (2017). https:\u002F\u002Fwww.coar-repositories.org\u002Ffiles\u002FNGR-Final-Formatted-Report-cc.pdf",{"doi":1428},{"id":18,"text":2108,"url":2109,"identifiers":2110},"Confederation of Open Access Repositories: COAR community framework for best practices in repositories. Technical Report Version 1, Zenodo (2020). https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.4110829","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.4110829",{"doi":2111},"10.5281\u002Fzenodo.4110829",{"id":18,"text":2113,"url":2114,"identifiers":2115},"Lin, D., Crabtree, J., Dillo, I., Downs, R.R., Edmunds, R., Giaretta, D., De Giusti, M., L’Hours, H., Hugo, W., Jenkyns, R., Khodiyar, V., Martone, M.E., Mokrane, M., Navale, V., Petters, J., Sierman, B., Sokolova, D.V., Stockhause, M., Westbrook, J.: The TRUST Principles for digital repositories. Sci. Data 7(1), 144 (2020). https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41597-020-0486-7","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41597-020-0486-7",{"mag":2116,"pmc":2117,"openalex":2118,"pm":2119,"doi":2120},"3024722698","7224370","W3024722698","32409645","10.1038\u002Fs41597-020-0486-7",{"id":18,"text":2122,"url":2123,"identifiers":2124},"Neylon, C., Bijsterbosch, M., Dunning, A., Kramer, B., De Rijcke, S., Tatum, C., Waltman, L.: An open knowledge base for the Netherlands: report of a community workshop. Technical report, Zenodo (2021). https:\u002F\u002Fdoi.org\u002F10.5281\u002FZENODO.4893803","https:\u002F\u002Fzenodo.org\u002Frecord\u002F4893803",{"mag":2125,"openalex":2126,"doi":2127},"3208788801","W3208788801","10.5281\u002Fzenodo.4893803",{"id":2129,"createTime":2130,"updateTime":2131,"relativeEntities":2132,"slug":2133,"properties":2134,"entityType":119,"verifyStatus":120,"verifyTime":2143,"verifyNote":122,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":2144,"fullTextUrl":18,"authors":2145,"publicationType":187,"publisherRelationship":2178,"citationCount":2225,"citationInfo":2226,"publishDate":2229,"publishYear":2227,"citationAnalyzeStatus":17,"lastCitationAnalyze":2230,"indexDatabases":2231,"openAccess":18,"references":2232,"isForceReanalyzing":240},"53a74107-aae2-4c19-800e-553a041c94e7","2023-12-28T07:44:09.987+00:00","2025-07-24T14:38:14.558+00:00",[],"ALOCOM-a-generic-content-model-for-learning-objects",{"abstract":2135,"title":2137,"gsPaper":2139,"doi":2141},{"EN":2136},"e-Learning organizations are focusing heavily on learning content reusability. The ultimate objective is a learning object economy characterized by searchable digital libraries of reusable learning objects that can be exchanged and reused across various learning systems. To enable such approach, basic questions of learning content interoperability need to be addressed. This paper investigates the interoperation of learning content defined according to different specifications. A number of content models are reviewed that define learning objects and their components. On the basis of a comparative analysis, the content models are mapped to a generic model for learning objects to address interoperability questions and to enable share and reuse on a global scale.",{"EN":2138},"ALOCOM: a generic content model for learning objects",{"VOID":2140},"[\"5505358364812868239\"]",{"VOID":2142},"10.1007\u002Fs00799-008-0039-8","2024-04-29T05:52:48.706+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs00799-008-0039-8",[2146,2163],{"id":2147,"sortIndex":19,"researcher":18,"roles":2148,"affiliations":2149,"properties":2158,"displayName":2160,"givenName":18,"familyName":18},"25beb538-7f32-4d72-a92e-db9a0a82df3b",[128],[2150],{"id":2151,"sortIndex":19,"affiliation":2152,"properties":18},"89a925bc-e88c-49eb-87b4-cbd5ccac765f",{"id":2151,"createTime":18,"updateTime":18,"relativeEntities":2153,"slug":18,"properties":2154,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2157,"statistic":18},[],{"title":2155},{"VI":2156},"Department of Computer Science, K.U. Leuven, Leuven, Belgium",[],{"title":2159,"gsAuthor":2161},{"VI":2160},"Katrien Verbert",{"VOID":2162},"[\"t5cgwVAAAAAJ\"]",{"id":2164,"sortIndex":83,"researcher":18,"roles":2165,"affiliations":2166,"properties":2173,"displayName":2175,"givenName":18,"familyName":18},"a063540d-818d-4a58-a979-48be5f51e2b8",[128],[2167],{"id":2151,"sortIndex":19,"affiliation":2168,"properties":18},{"id":2151,"createTime":18,"updateTime":18,"relativeEntities":2169,"slug":18,"properties":2170,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2172,"statistic":18},[],{"title":2171},{"VI":2156},[],{"title":2174,"gsAuthor":2176},{"VI":2175},"Erik Duval",{"VOID":2177},"[\"PZURMD0AAAAJ\"]",{"url":2144,"publisher":2179,"properties":2220},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":2180,"slug":10,"properties":2181,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":2184,"manageAffiliations":2189,"indexDatabases":2200,"url":18,"thumbnailPath":18,"statistic":2215,"gsStatistic":18,"type":18,"analyzePriority":18},[],{"issn":2182,"title":2183},{"VOID":13},{"EN":15},[2185],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":2186,"label":2187,"description":2188,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},[2190,2195],{"id":29,"createTime":18,"updateTime":18,"relativeEntities":2191,"slug":18,"properties":2192,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2194,"statistic":18},[],{"title":2193},{"EN":33},[],{"id":36,"createTime":18,"updateTime":18,"relativeEntities":2196,"slug":18,"properties":2197,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2199,"statistic":18},[],{"title":2198},{"EN":40},[42],[2201,2208],{"id":45,"indexDatabase":2202,"url":56,"indexYears":57,"academicFieldIds":2207,"indexDatabaseRanking":60},{"id":47,"createTime":18,"updateTime":18,"relativeEntities":2203,"label":2204,"description":2205,"key":53,"publicationTags":2206,"standard":18},[],{"EN":50,"VI":50},{"EN":50,"VI":52},[55],[59],{"id":62,"indexDatabase":2209,"url":75,"indexYears":18,"academicFieldIds":2214,"indexDatabaseRanking":18},{"id":64,"createTime":18,"updateTime":18,"relativeEntities":2210,"label":2211,"description":2212,"key":71,"publicationTags":2213,"standard":18},[],{"EN":67,"VI":67},{"EN":69,"VI":70},[73,74],[77],{"impactFactor":19,"impactFactorByYear":2216,"i10Index":80,"i10IndexLast5Year":19,"totalPublication":81,"totalPublicationByYear":2217,"totalCitation":86,"totalCitationByYear":2218,"totalCitationPerPublication":93,"totalCitationPerPublicationByYear":2219,"hindexLast5Year":80,"hindex":80},{},{"1997":83,"1998":84,"1999":83,"2000":85,"2002":84},{"1997":88,"1998":89,"1999":90,"2000":91,"2002":92},{"1997":88,"1998":95,"1999":90,"2000":96,"2002":97},{"pages":2221,"volume":2223},{"VOID":2222},"41-63",{"VOID":2224},"9",78,{"total":2225,"publishYear":2227,"statisticByYear":2228},2008,{"2008":84,"2009":385,"2010":347,"2011":440,"2012":385,"2013":401,"2014":401,"2015":385,"2016":84,"2017":347,"2018":385,"2019":84,"2020":84,"2021":385,"2022":175,"2023":84,"2024":84,"2025":83},"2008-06-11","2025-07-24T14:38:14.557+00:00",[73,60],[2233,2237,2240,2244,2247,2250,2253,2256,2259,2262,2265,2268,2272,2275,2279,2282,2285,2288,2291,2295,2299,2303,2306,2309,2312,2315,2318,2322,2326,2329,2333,2337,2341,2344,2347,2350,2353,2356,2362,2365,2369,2372,2375,2378,2381,2384],{"id":18,"text":2234,"url":2235,"identifiers":2236},"Advanced Distributed Learning (ADL). http:\u002F\u002Fwww.adlnet.org (2007). Accessed 30 September 2007","http:\u002F\u002Fwww.adlnet.org",{},{"id":18,"text":2238,"url":18,"identifiers":2239},"Ballstaedt, S.-P.: Wissensvermittlung die Gestaltung von Lernmaterial. Weinheim, Beltz PsychologieVerslagsUnion (1997)",{},{"id":18,"text":2241,"url":2242,"identifiers":2243},"Barrit, C., Lewis, D., Wieseler, W.: CISCO Systems Reusable Information Object Strategy Version 3.0. Cisco Whitepaper. http:\u002F\u002Fwww.cisco.com\u002Fwarp\u002Fpublic\u002F779\u002Fibs\u002Fsolutions\u002Flearning\u002Fwhitepapers\u002Fel_cisco_rio.pdf (1999). Accessed 30 September 2007","http:\u002F\u002Fwww.cisco.com\u002Fwarp\u002Fpublic\u002F779\u002Fibs\u002Fsolutions\u002Flearning\u002Fwhitepapers\u002Fel_cisco_rio.pdf",{},{"id":18,"text":2245,"url":18,"identifiers":2246},"Bechhofer, S., van Harmelen, F., Hendler, J.A., Horrocks, I., McGuinness, D.L., Patel-Schneider, P.F., Stein, L.A., Dean, M., Schreiber, G. (eds.): OWL Web Ontology Language Reference, World Wide Web Consortium, Recommendation REC-owl-ref-20040210, February 2004",{},{"id":18,"text":2248,"url":18,"identifiers":2249},"Brooks, J., Jesukiewicz, P.: SCORM reuse: current reality, challenges, and best practices. In: Proceedings of the Interservice\u002FIndustry Training, Simulation, and Education Conference (I\u002FITSEC), Florida, 4–7 December 2006",{},{"id":1424,"text":2251,"url":1426,"identifiers":2252},"Buccella A., Cechic A., Brisaboa N.R.: An ontology approach to data integration. J. Comput. Sci. 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Harper Collins, New York (1990)",{"doi":1428},{"id":1424,"text":2266,"url":1426,"identifiers":2267},"Downes, S.: Learning objects: resources for distance education worldwide. Int. Rev. Res. Open Distance Learn. 2(1) (2001)",{"doi":1428},{"id":18,"text":2269,"url":2270,"identifiers":2271},"1484.12.1 IEEE LTSC Draft Standard for Learning Object Metadata http:\u002F\u002Fltsc.ieee.org\u002Fwg12\u002Ffiles\u002FLOM_1484_12_1_v1_Final_Draft.pdf (2002)","http:\u002F\u002Fltsc.ieee.org\u002Fwg12\u002Ffiles\u002FLOM_1484_12_1_v1_Final_Draft.pdf",{},{"id":1424,"text":2273,"url":1426,"identifiers":2274},"Duval, E., Hodgins, W.: A LOM research agenda. In: Hencsey, G., White, B., Chen, Y., Kovacs, L., Lawrence, S. (eds.) Proceedings of the 12th international conference on World Wide Web, Budapest, Hungary, pp. 659–667 (2003)",{"doi":1428},{"id":18,"text":2276,"url":2277,"identifiers":2278},"ELI. EDUCAUSE Learning Initiative. http:\u002F\u002Fwww.educause.edu\u002Feli (2007). Accessed 30 September 2007","http:\u002F\u002Fwww.educause.edu\u002Feli",{},{"id":18,"text":2280,"url":18,"identifiers":2281},"Fernandes, E., Madhour, H., Miniaoui, S., Forte, M.W.: Phoenix Tool: A Support to Semantic Learning Model. Workshop on Applications of Semantic Web Technologies for e-Learning (SW-EL@ICALT’05), Kaohsiung, Taiwan, 5–8 July 2005",{},{"id":1424,"text":2283,"url":1426,"identifiers":2284},"Gagne R.: The conditions of learning and theory of instruction. CBS College, New York (1985)",{"doi":1428},{"id":18,"text":2286,"url":18,"identifiers":2287},"Horn R.: Structured writing at Twenty-five. Perform. Instr. 32, 11–17 (1993)",{},{"id":1424,"text":2289,"url":1426,"identifiers":2290},"Horn R.E. (1998) Structured writing as a paradigm. In: Romiszowski A., Dills C. (eds). Instructional development: state of the art. Educational Technology Publications, Englewood Cliffs",{"doi":1428},{"id":18,"text":2292,"url":2293,"identifiers":2294},"IMS-CP. IMS Content Packaging. Information Model, Best Practice and Implementation Guide, XML Binding Schemas, Version 1.1.4 Final Specification, IMS Global Consortium Inc. http:\u002F\u002Fwww.imsglobal.org\u002Fcontent\u002Fpackaging (2007). Accessed 30 September 2007","http:\u002F\u002Fwww.imsglobal.org\u002Fcontent\u002Fpackaging",{},{"id":18,"text":2296,"url":2297,"identifiers":2298},"IMS Learning Design (IMS LD) Specification. http:\u002F\u002Fwww.imsglobal.org\u002Flearningdesign\u002F (2003)","http:\u002F\u002Fwww.imsglobal.org\u002Flearningdesign\u002F",{},{"id":18,"text":2300,"url":2301,"identifiers":2302},"ISO\u002FIEC 21000-2:2005. Information technology: multimedia framework (MPEG-21) Part 2: Digital Item Declaration. http:\u002F\u002Fstandards.iso.org\u002Fittf\u002FPubliclyAvailableStandards\u002Fc041112_ISO_IEC_21000-2_2005(E).zip (2007). Accessed 30 September 2007","http:\u002F\u002Fstandards.iso.org\u002Fittf\u002FPubliclyAvailableStandards\u002Fc041112_ISO_IEC_21000-2_2005(E).zip",{},{"id":18,"text":2304,"url":18,"identifiers":2305},"L’Allier, J.J.: Frame of reference: NETg’s map to the products, their structure and core beliefs. NetG whitepaper. Cited in Polsani, Pithamber R. (2003) The Use and Abuse of Reusable Learning Objects. J. Digit. Inf. 3(4)",{},{"id":18,"text":2307,"url":18,"identifiers":2308},"Lenski, W., Wette-Roch, E.: The TRIAL-SOLUTION approach to document re-use principles and realization. In: Proceedings of Electronic Media in Mathematics, Coimbra, 13–15 September 2001",{},{"id":18,"text":2310,"url":18,"identifiers":2311},"Löser, A., Grune, C., Hoffmann, M.: A didactic model, definition of learning objects and selection of metadata for an online curriculum. In: Proceedings of the International Workshop of Interactive Computer Aided Learning (ICL), Villach, Austria 2002",{},{"id":18,"text":2313,"url":18,"identifiers":2314},"Mager R.F.: Preparing instructional objectives, 2nd edn. David S. Lake, Belmont (1984)",{},{"id":1424,"text":2316,"url":1426,"identifiers":2317},"Merrill, M.D.: Component display theory. In: Reigeluth, C.M. (eds.) Instructional design theories and models. Erlbaum Associates, Hillsdale, NJ (1983)",{"doi":1428},{"id":18,"text":2319,"url":2320,"identifiers":2321},"Metadata Encoding and Transmission Standard (METS). http:\u002F\u002Fwww.loc.gov\u002Fstandards\u002Fmets\u002Fmets-home.html (2007). Accessed 30 September 2007","http:\u002F\u002Fwww.loc.gov\u002Fstandards\u002Fmets\u002Fmets-home.html",{},{"id":18,"text":2323,"url":2324,"identifiers":2325},"Navy Integrated Learning Environment (Navy ILE) Introduction. https:\u002F\u002File-help.nko.navy.mil\u002File\u002F (2007). Accessed 30 September 2007","https:\u002F\u002File-help.nko.navy.mil\u002File\u002F",{},{"id":1424,"text":2327,"url":1426,"identifiers":2328},"Pazandak P., Srivastava J.: Evaluating object DBMSs for multimedia. IEEE Multimed. 4(3), 34–49 (1997)",{"doi":1428},{"id":18,"text":2330,"url":2331,"identifiers":2332},"ProLearn: Prolearn Network of Excellence on professional learning. http:\u002F\u002Fwww.prolearn-project.org\u002F (2007). Accessed 30 September 2007","http:\u002F\u002Fwww.prolearn-project.org\u002F",{},{"id":18,"text":2334,"url":2335,"identifiers":2336},"Resource Aggregation Model for Learning, Education and Training (RAMLET). http:\u002F\u002Fwww.ieeeltsc.org\u002Fwg11CMI\u002Framlet\u002FPub\u002F. Accessed 30 September 2007","http:\u002F\u002Fwww.ieeeltsc.org\u002Fwg11CMI\u002Framlet\u002FPub\u002F",{},{"id":18,"text":2338,"url":2339,"identifiers":2340},"Reusable Learning. http:\u002F\u002Fwww.reusablelearning.org (2007). 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Evaluation und Didaktik, München (2003)",{"doi":1428},{"id":18,"text":2354,"url":2235,"identifiers":2355},"Sharable Content Object Reference Model (SCORM): 2nd edn. http:\u002F\u002Fwww.adlnet.org (2004). Accessed 30 September 2007",{},{"id":2357,"text":2358,"url":2359,"identifiers":2360},"92b868c1-2c84-43d2-9468-765acc1448ff","Su X., Gulla J.A.: An information retrieval approach to ontology mapping. Data Knowl. Eng. 58(1), 47–69 (2006)","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0169023X05000777",{"doi":2361},"10.1016\u002Fj.datak.2005.05.012",{"id":1424,"text":2363,"url":1426,"identifiers":2364},"Süβ, C., Kammerl, R., Freitag, B.: A teachware management framework for multiple teaching strategies. In: Bourdeau, J., Heller, R. (eds.) Proceedings of the 12th ED-MEDIA 2000 World Conference on Educational Multimedia, Hypermedia and Telecommunications, Montreal, QC, Canada, pp. 1101–1106, 26 June–1 July 2000",{"doi":1428},{"id":18,"text":2366,"url":2367,"identifiers":2368},"Tan, G.H.: Getting Started with Learning Objects. Publication incorporated into SeLF (Singapore e-Learning Framework). http:\u002F\u002Fole.tp.edu.sg\u002Fcourseware\u002Fteaching_guide\u002Fresources\u002Farticle\u002Fgekhua\u002FGetting%20Started%20with%20LO.pdf (2002). Accessed 30 September 2007","http:\u002F\u002Fole.tp.edu.sg\u002Fcourseware\u002Fteaching_guide\u002Fresources\u002Farticle\u002Fgekhua\u002FGetting%20Started%20with%20LO.pdf",{},{"id":1424,"text":2370,"url":1426,"identifiers":2371},"Ullrich C.: The learning-resource-type is dead, long live the learning-resource-type!. Learn. Objects Learn. Des. 1(1), 7–15 (2005)",{"doi":1428},{"id":1424,"text":2373,"url":1426,"identifiers":2374},"Verbert, K., Duval, E.: Towards a global architecture for learning objects: a comparative analysis of learning object content models. In: Cantoni, L., McLoughlin, C. (eds.) Proceedings of the 16th ED-MEDIA 2004 World Conference on Educational Multimedia, Hypermedia and Telecommunications, Lugano, Switzerland, pp. 202–209 (2004)",{"doi":1428},{"id":1424,"text":2376,"url":1426,"identifiers":2377},"Verbert, K., Jovanovic, J., Gasevic, D., Duval, E.: Repurposing Learning object Components. In: Spyns, P., Duval, E., de Moor, A., Aroyo, L. (eds.) Proceedings of WOSE05: OTM 2005 Workshop on Ontologies, Semantics and E-Learning, Agia Napa, Cyprus, November 3 2005, pp. 1169–1178. Springer, Berlin (2005)",{"doi":1428},{"id":18,"text":2379,"url":18,"identifiers":2380},"Wagner, E.D.: Steps to creating a content strategy for your organization. e-Learn. Dev. J. (2002)",{},{"id":18,"text":2382,"url":18,"identifiers":2383},"Wiley, D.A.: Connecting learning objects to instructional design theory: a definition, a metaphor, and a taxonomy. The instructional use of learning objects, Bloomington (2002)",{},{"id":18,"text":2385,"url":2386,"identifiers":2387},"Wiley, D.A.: The learning objects literature. http:\u002F\u002Fopencontent.org\u002Fblog\u002Fwp-content\u002Fuploads\u002F2007\u002F07\u002Fwiley-lo-review-final.pdf. Accessed 10 September 2007","http:\u002F\u002Fopencontent.org\u002Fblog\u002Fwp-content\u002Fuploads\u002F2007\u002F07\u002Fwiley-lo-review-final.pdf",{},{"id":2389,"createTime":2390,"updateTime":2391,"relativeEntities":2392,"slug":2393,"properties":2394,"entityType":119,"verifyStatus":120,"verifyTime":2391,"verifyNote":122,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":2400,"fullTextUrl":18,"authors":2401,"publicationType":187,"publisherRelationship":2469,"citationCount":18,"citationInfo":18,"publishDate":2515,"publishYear":1206,"citationAnalyzeStatus":17,"lastCitationAnalyze":18,"indexDatabases":2516,"openAccess":18,"references":18,"isForceReanalyzing":240},"91dd7498-14b1-41f3-b53d-3c9b2b99b80a","2023-12-08T08:03:16.352+00:00","2025-02-26T21:47:02.622+00:00",[],"Usability-study-of-digital-libraries-ACM-IEEE-CS-NCSTRL-NDLTD",{"title":2395,"doi":2397,"abstract":2398},{"EN":2396},"Usability study of digital libraries: ACM, IEEE-CS, NCSTRL, NDLTD",{"VOID":679},{"EN":2399},"If digital libraries are to be used effectively, their user interfaces should be tested and enhanced. We observed 48 participants as they worked with the following digital libraries: ACM, IEEE-CS, NCSTRL, and NDLTD. We discuss how the features of these digital libraries influence the subjects’ efforts to perform search and retrieval tasks. Data analysis indicates that the IEEE-CS digital library was rated the best overall and NDLTD had the best search time. We present user recommendations and propose a taxonomy of features that we believe are essential for the design of future digital libraries. Noteworthy is the observation that users’ judgements on the importance of different features varied widely between the beginning and end of their test sessions.","http:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs007990050044",[2402,2417,2430,2443,2456],{"id":2403,"sortIndex":19,"researcher":18,"roles":2404,"affiliations":2405,"properties":2414,"displayName":2416,"givenName":18,"familyName":18},"a15aef04-8a8b-40d2-910a-39827d0fa7e8",[128],[2406],{"id":2407,"sortIndex":19,"affiliation":2408,"properties":18},"5c628300-2556-4d59-8747-6deea531e293",{"id":2407,"createTime":18,"updateTime":18,"relativeEntities":2409,"slug":18,"properties":2410,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2413,"statistic":18},[],{"title":2411},{"VI":2412},"Department of Computer Science, Virginia Polytechnic Institute & State University, Blacksburg, VA 24061, USA; E-mail: {cseals, hharley, hmamidi, fox}@vt.edu, USA",[],{"title":2415},{"VI":2416},"Rekha Kengeri",{"id":2418,"sortIndex":83,"researcher":18,"roles":2419,"affiliations":2420,"properties":2427,"displayName":2429,"givenName":18,"familyName":18},"7ed226d3-4aaf-4ca4-8b65-9a0dd9c5f52e",[128],[2421],{"id":2407,"sortIndex":19,"affiliation":2422,"properties":18},{"id":2407,"createTime":18,"updateTime":18,"relativeEntities":2423,"slug":18,"properties":2424,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2426,"statistic":18},[],{"title":2425},{"VI":2412},[],{"title":2428},{"VI":2429},"Cheryl D. 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In: Proceedings of the 2000 international conference on digital libraries: research and practice, Kyoto, Japan\u002FLos Alamitos, CA. http:\u002F\u002Fwww.ipsi.fraunhofer.de\u002Fdelite\u002FPublications\u002FAbstracts\u002Fa-QiuHemmjeNeuhold00c.html\nSteinmetz A, Kienzle M (2001) The e-Seminar lecture recording and distribution system. In: Proceedings of SPIE MultiMedia Computing and Networking 2001 (MMCN), San Jose, CA, vol 4312. http:\u002F\u002Fbookstore.spie.org\u002Fcgi-bin\u002Ftoc.pl?volume=4312&journal=SPIE\nWactlar HD (2000) Informedia – search and summarization in the video medium. 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