A survey towards an integration of big data analytics to big insights for value-creation
Tóm tắt
Từ khóa
Tài liệu tham khảo
Abbasi, 2016, Big data research in information systems: toward an inclusive research agenda, Journal of the Association for Information Systems, 17, 1, 10.17705/1jais.00423
ACM, Digital Library. http://www.acm.org/dl/ Accessed 30 Dec 2017.
Addo-Tenkorang, 2016, Big data applications in operations/supply-chain management: A literature review, Computers & Industrial Engineering, 101, 528, 10.1016/j.cie.2016.09.023
Agrawal, 2015, Neural network techniques for cancer prediction: a survey, Procedia Computer Science, 60, 769, 10.1016/j.procs.2015.08.234
Ahmed, 2017, The role of big data analytics in Internet of Things, Computer Networks, 129, 459, 10.1016/j.comnet.2017.06.013
Airoldi, 2008, Mixed membership stochastic blockmodels, Journal of Machine Learning Research, 9, 1981
Al Nuaimi, 2015, Applications of big data to smart cities, Journal of Internet Services and Applications, 6, 25, 10.1186/s13174-015-0041-5
Alowibdi, 2014, Detecting deception in online social networks, 383
Alsheikh, 2016, Mobile big data analytics using deep learning and apache spark, IEEE Network, 30, 22, 10.1109/MNET.2016.7474340
An, 2012, Image super-resolution by extreme learning machine, 2209
Archenaa, 2015, A survey of big data analytics in healthcare and government, Procedia Computer Science, 50, 408, 10.1016/j.procs.2015.04.021
Armstrong, 2014
2013
Assuncao, 2015, Big data computing and clouds: Trends and future directions, Journal of Parallel and Distributed Computing, 79, 3, 10.1016/j.jpdc.2014.08.003
Asur, 2010, Predicting the future with social media, 1, 492
Apache Spark, 2014. https://spark.apache.org/ Accessed 20 Dec 2017.
Apache SparkR. https://docs.databricks.com/spark/latest/sparkr/overview.html/ Accessed 20 Dec 2017.
Apache MapReduce, 2008. https://hadoop.apache.org/docs/r1.2.1/mapred_tutorial.html/ Accessed 20 Dec 2017.
Apache Mahout, 2011. https://mahout.apache.org/ Accessed 20 Dec 2017.
Apache MOA, 2011. https://en.wikipedia.org/wiki/Massive_Online_Analysis/ Accessed 20 Dec 2017.
Apache Giraph. http://giraph.apache.org/ Accessed 20 Dec 2017.
Baker, 2009, The state of educational data mining in 2009: A review and future visions, Journal of Educational Data Mining, 1, 3
Balakrishnan, 2010, On the predictive ability of narrative disclosures in annual reports, European Journal of Operational Research, 202, 789, 10.1016/j.ejor.2009.06.023
Balkan, 2015, Video analytics in market research, Information Systems Management, 32, 192, 10.1080/10580530.2015.1044337
Barnaghi, 2013, From data to actionable knowledge: Big data challenges in the web of things, IEEE Intelligent Systems, 28, 6, 10.1109/MIS.2013.142
Bashir, 2016, Towards an IoT Big Data Analytics Framework: Smart Buildings Systems, 1325
Basu, 2013, Five pillars of prescriptive analytics success, Analytics magazine, 8
Batarseh, 2016, Assessing the quality of service using big data analytics: With application to healthcare, Big Data Research, 4, 13, 10.1016/j.bdr.2015.10.001
Becker, 2016, Big data usage, 143
Bendre, 2016, Big data in precision agriculture through ICT: Rainfall prediction using neural network approach, 165
Bengio, 2013, Deep learning of representations: Looking forward, 1
Bhimani, 2014, Digitisation,‘Big Data'and the transformation of accounting information, Accounting and Business Research, 44, 469, 10.1080/00014788.2014.910051
Bilal, 2016, Big Data in the construction industry: A review of present status, opportunities, and future trends, Advanced Engineering Informatics, 30, 500, 10.1016/j.aei.2016.07.001
Bloor, 2011, Big data analytics – this time it's personal, The Bloor Group
Borkar, 2012, Big data platforms: What's next?, XRDS: Crossroads, The ACM Magazine for Students, 19, 44, 10.1145/2331042.2331057
Brereton, 2007, Lessons from applying the systematic literature review process within the software engineering domain, Journal of systems and software, 80, 571, 10.1016/j.jss.2006.07.009
Butcher, 2013, Reservoir computing and extreme learning machines for non-linear time-series data analysis, Neural Networks, 38, 76, 10.1016/j.neunet.2012.11.011
Buyya, 2016
Buza, 2014, Storage-optimizing clustering algorithms for high-dimensional tick data, Expert Systems with Applications, 41, 4148, 10.1016/j.eswa.2013.12.046
Cao, 2015, Big data analytics in financial statement audits, Accounting Horizons, 29, 423, 10.2308/acch-51068
Casado, 2015, Emerging trends and technologies in big data processing, Concurrency and Computation: Practice and Experience, 27, 2078, 10.1002/cpe.3398
Castillo, 2005, Effective web crawling, 39, 55
Cerchiello, 2016, Big data analysis for financial risk management, Journal of Big Data, 3, 1, 10.1186/s40537-016-0053-4
Cetin, 2016, Meeting revenue management challenges: Knowledge, skills and abilities, International Journal of Hospitality Management, 57, 132, 10.1016/j.ijhm.2016.06.008
Chandola, 2009, Anomaly detection: A survey, ACM computing surveys (CSUR), 41, 1, 10.1145/1541880.1541882
Chaturvedi, 2012, Data mining techniques for design of its student models, 218
Chen, 2014, Data-intensive applications, challenges, techniques and technologies: A survey on Big Data, Information Sciences, 275, 314, 10.1016/j.ins.2014.01.015
Chen, 2016, Agile big data analytics for web-based systems: An architecture-centric approach, IEEE Transactions on Big Data, 2, 234, 10.1109/TBDATA.2016.2564982
Chen, 2012, Business intelligence and analytics: From big data to big impact, MIS quarterly, 36, 1165, 10.2307/41703503
Chen, 2013, Big data challenge: A data management perspective, Frontiers of Computer Science, 7, 157, 10.1007/s11704-013-3903-7
Chen, 2014, Big data: A survey, Mobile Networks and Applications, 19, 171, 10.1007/s11036-013-0489-0
Chen, 2014, Big data deep learning: Challenges and perspectives, IEEE access, 2, 514, 10.1109/ACCESS.2014.2325029
Cheptsov, 2015, Leveraging high-performance computing infrastructures to web data analytic applications by means of message-passing interface, 4, 167
Chung, 2014, BizPro: Extracting and categorizing business intelligence factors from textual news articles, International Journal of Information Management, 34, 272, 10.1016/j.ijinfomgt.2014.01.001
Colak, 2012, Data mining and wind power prediction: A literature review, Renewable Energy, 46, 241, 10.1016/j.renene.2012.02.015
Cox, 1997, Application-controlled demand paging for out-of-core visualization
Crawley, 2014, Analytics in empirical/archival financial accounting research, Business Horizons, 57, 583, 10.1016/j.bushor.2014.05.002
De Mauro, 2016, A formal definition of big data based on its essential features, Library Review, 65, 122, 10.1108/LR-06-2015-0061
Dean, 2008, MapReduce: Simplified data processing on large clusters, Communications of the ACM, 51, 107, 10.1145/1327452.1327492
Ding, 2015, Extreme learning machine: Algorithm, theory and applications, Artificial Intelligence Review, 44, 103, 10.1007/s10462-013-9405-z
Dolin, 2015, Health level seven interoperability strategy: Big data, incrementally structured, Methods of information in medicine, 54, 75, 10.3414/ME14-01-0030
Dong, 2014, Towards unified object detection and semantic segmentation, 8693, 299
Eagle, 2009, Inferring friendship network structure by using mobile phone data, Proceedings of the national academy of sciences, 106, 15274, 10.1073/pnas.0900282106
Edwards, 2016, Using knowledge management to give context to Analytics and big data and reduce strategic risk, Procedia Computer Science, 99, 36, 10.1016/j.procs.2016.09.099
Fahad, 2014, A survey of clustering algorithms for big data: Taxonomy and empirical analysis, IEEE Transactions on Emerging Topics in Computing, 2, 267, 10.1109/TETC.2014.2330519
Fanning, 2014, Big data: New opportunities for M&A, Journal of Corporate Accounting & Finance, 25, 27, 10.1002/jcaf.21919
Fayyad, 1996, From data mining to knowledge discovery in databases, AI Magazine, 17, 37
Fiosina, 2013, Big data processing and mining for next generation intelligent transportation systems, Journal Teknologi, 63, 21
Fogelman-Soulié, 2016, Implementing big data analytics projects in business, 141
Francik, 2016, Present trends in research on application of artificial neural networks in agricultural engineering, Agricultural Engineering, 20, 15, 10.1515/agriceng-2016-0060
Fulantelli, 2013, A semantic approach to mobile learning analytics, 287
Gamble, 2011, Quality, trust, and utility of scientific data on the web: Towards a joint model, 1
Gandomi, 2015, Beyond the hype: Big data concepts, methods, and analytics, International Journal of Information Management, 35, 137, 10.1016/j.ijinfomgt.2014.10.007
Gantz, 2011, Extracting value from chaos, IDC iview, 1142, 1
Gartner, Inc., (2011). Pattern-based strategy: getting value from big data. http://www.gartner.com/it/page.jsp?id=1731916 Accessed 12 Feb 2016.
Google Scholar, Digital library. http://www.scholar.google.co.in/ Accessed 20 Dec 2017.
Gubbi, 2013, Internet of Things (IoT): A vision, architectural elements, and future directions, Future generation computer systems, 29, 1645, 10.1016/j.future.2013.01.010
Guo, 2016, Deep learning for visual understanding: A review, Neurocomputing, 187, 27, 10.1016/j.neucom.2015.09.116
Hadoop, A. (2011). Apache hadoop. http://omeroztat.com/docs/Hadoop.pdf/ Accessed 12 Nov 2017.
Hagel, 2015, Bringing analytics to life, Journal of Accountancy, 219, 24
Hagstrom, 2012, High-performance analytics fuels innovation and inclusive growth: Use big data, hyper connectivity and speed to intelligence to get true value in the digital economy, Journal of Advanced Analytics, 2, 3
Haile, 2016, Value creation in software service platforms, Futur Generation Computer Systems, 55, 495, 10.1016/j.future.2015.09.029
Hänel, 2015, Linking operational business intelligence with value-based business requirements, 9373, 147
Hayes, P. J., & Carbonell, J. G. (1983). A tutorial on techniques and applications for natural language processing, 1–14. http://repository.cmu.edu/cgi/viewcontent.cgi?article=2483&context=compsci/ Accessed 12 Nov 2017.
Hazen, 2016, Big Data and predictive analytics for supply chain sustainability y: A theory-driven research agenda, Computers & Industrial Engineering, 101, 592, 10.1016/j.cie.2016.06.030
He, 2014, Fast face recognition via sparse coding and extreme learning machine, Cognitive Computation, 6, 264
Himmelblau, 2000, Applications of artificial neural networks in chemical engineering, Korean journal of chemical engineering, 17, 373, 10.1007/BF02706848
Hirschberg, 2010, You're as Sick as You Sound”: Using computational approaches for modeling speaker state to gauge illness and recovery, 305
Hoffman, 2014, LSDA: Large scale detection through adaptation, 3536
Hortonworks, (2011). http://hortonworks.com/products/hortonworks-sandbox/ Accessed 12 Nov 2017.
HP-HAVEn, (2013). https://en.wikipedia.org/wiki/HP_Autonomy/ Accessed 12 Nov 2017.
Hu, 2014, Toward scalable systems for big data analytics: A technology tutorial, IEEE access, 2, 652, 10.1109/ACCESS.2014.2332453
Hu, 2015, Design of a web-based application of the coupled multi-agent system model and environmental model for watershed management analysis using Hadoop, Environmental Modeling & Software, 70, 149, 10.1016/j.envsoft.2015.04.011
Huang, 2011, Extreme learning machines: A survey, International Journal of Machine Learning and Cybernetics, 2, 107, 10.1007/s13042-011-0019-y
Huang, 2015, Trends in extreme learning machines: A review, Neural Networks, 61, 32, 10.1016/j.neunet.2014.10.001
H2O. Big Data, 2011. https://www.h2o.ai/ Accessed 12 Dec 2017.
IEEE Xplore. Digital Library. http://www.ieeexplore.ieee.org/ Accessed 30 Dec 2017.
Infobright, (2005). http://www.infobright.com/ Accessed 20 Dec 2017.
Injadat, 2016, Data mining techniques in social media: A survey, Neurocomputing, 214, 654, 10.1016/j.neucom.2016.06.045
Iqbal, 2017, Big data analytics and computational intelligence for cyber–physical systems: Recent trends and state of the art applications, Future Generation Computer Systems, 1
Jabbour, 2013, Environmental training in organisations: From a literature review to a framework for future research, Resources, Conservation and Recycling, 74, 144, 10.1016/j.resconrec.2012.12.017
Jha, 2007, Artificial neural networks and its applications, IARI, New Delhi, 1
Jiang, 2013, Applications and implementation of decomposition storage model (DSM) in paas of agricultural, 420, 34
Jin, 2015, Significance and challenges of big data research, Big Data Research, 2, 59, 10.1016/j.bdr.2015.01.006
Jukic, 2015, Augmenting data warehouses with Big Data, Information Systems Management, 32, 200, 10.1080/10580530.2015.1044338
Kambatla, 2014, Trends in big data analytics, Journal of Parallel and Distributed Computing, 74, 2561, 10.1016/j.jpdc.2014.01.003
Khan, 2017, A survey on scholarly data: From big data perspective, Information Processing & Management, 53, 923, 10.1016/j.ipm.2017.03.006
Khan, 2015, Towards cloud based big data analytics for smart future cities, Journal of Cloud Computing, 4, 2, 10.1186/s13677-015-0026-8
Krizhevsky, 2012, Imagenet classification with deep convolutional neural networks, 1097
Kshetri, 2014, The emerging role of Big Data in key development issues: Opportunities, challenges, and concerns, Big Data & Society, 1, 1, 10.1177/2053951714564227
Kshetri, 2016, Big data's role in expanding access to financial services in China, International Journal of Information Management, 36, 297, 10.1016/j.ijinfomgt.2015.11.014
Laurila, 2012, The mobile data challenge: Big data for mobile computing research, 1
Lawson, 2013, Focusing accounting curricula on students' long-run careers: Recommendations for an integrated competency-based framework for accounting education, Issues in Accounting Education, 29, 295, 10.2308/iace-50673
Lazer, 2009, Life in the network: The coming age of computational social science, Science (New York, NY), 323, 721, 10.1126/science.1167742
Lee, 2014, Recent advances and trends of cyber-physical systems and big data analytics in industrial informatics, 1
Lee, 2017, Predictive big data analytics and cyber physical systems for TES systems, 97
Lee, 2013, Agricultural production system based on IOT, 833
Lee, 2012, Leveraging input and output structures for joint mapping of epistatic and marginal eQTLs, Bioinformatics, 28, i137, 10.1093/bioinformatics/bts227
Li, 2013, 1
Li, 2013, Influence diffusion dynamics and influence maximization in social networks with friend and foe relationships, 657
Liao, 2012, Data mining techniques and applications–A decade review from 2000 to 2011, Expert systems with applications, 39, 11303, 10.1016/j.eswa.2012.02.063
Liu, 2016, Rethinking big data: A review on the data quality and usage issues, ISPRS Journal of Photogrammetry and Remote Sensing, 115, 134, 10.1016/j.isprsjprs.2015.11.006
Liu, 2017, A survey of deep neural network architectures and their applications, Neurocomputing, 234, 11, 10.1016/j.neucom.2016.12.038
Liu, 2015, Deep index for accurate and efficient image retrieval, 43
Majumdar, 2017, Analysis of agriculture data using data mining techniques: Application of big data, Journal of Big Data, 4, 20, 10.1186/s40537-017-0077-4
Manyika, 2011, Big data: The next frontier for innovation, competition and productivity
Marjani, 2017, Big IoT data analytics: Architecture, opportunities, and open research challenges, IEEE Access, 5, 5247, 10.1109/ACCESS.2017.2689040
Marquez, 2000, Machine learning and natural language processing
Merino, 2016, A data quality in use model for big data, Future Generation Computer Systems, 63, 123, 10.1016/j.future.2015.11.024
Mikalef, 2017, Big data analytics capabilities: A systematic literature review and research agenda, Information Systems and e-Business Management, 1
Mithas, 2010, What is your digital business strategy?, IT professional, 12, 4, 10.1109/MITP.2010.154
Moss, 2012, A linked data approach to assessing medical data, 1
Najafabadi, 2015, Deep learning applications and challenges in big data analytics, Journal of Big Data, 2, 1, 10.1186/s40537-014-0007-7
Neocleous, 2002, Artificial neural network learning: A comparative review, Methods and Applications of Artificial Intelligence, 300
Ngai, 2009, Application of data mining techniques in customer relationship management: A literature review and classification, Expert systems with applications, 36, 2592, 10.1016/j.eswa.2008.02.021
Nino, 2015, Entendiendo el big data: Antecedentes, Origen Y Desarrollo Posterior, DYNA New Technologies, 2, 1
2012
Ortiz-Rangel, 2015, Towards a smart city: Design of a domestic smart grid, 863
Oussous, 2017, Big data technologies: A survey, Journal of King Saud University-Computer and Information Sciences, 1
Ouyang, 2014, Multi-source deep learning for human pose estimation, 2329
Pääkkönen, 2015, Reference architecture and classification of technologies, products and services for big data systems, Big Data Research, 2, 166, 10.1016/j.bdr.2015.01.001
Peña-Ayala, 2014, Educational data mining: A survey and a data mining-based analysis of recent works, Expert systems with applications, 41, 1432, 10.1016/j.eswa.2013.08.042
Phillips, 2001, Ontology-guided knowledge discovery in databases, 123
Pivotal big data suite, (2016). http://pivotal.io/big-data/pivotal-big-data-suite/ Accessed 30 Dec 2017.
Pole, 2016, A recent study of emerging tools and technologies boosting big data analytics, 29
PricewaterhouseCoopers, (2015). Data driven: What students need to succeed in a rapidly changing business world. White Paper. https://www.pwc.com/us/en/faculty-resource/assets/PwC-Data-driven-paper-Feb2015.pdf/ Accessed 23 May 2016.
Qiu, 2016, A survey of machine learning for big data processing, EURASIP Journal on Advances in Signal Processing, 2016, 1
Raghupathi, 2014, Big data analytics in healthcare: Promise and potential, Health Information Science and Systems, 2, 3, 10.1186/2047-2501-2-3
Ramannavar, 2016, Big Data and analytics—A Journey through basic concepts to research issues, 398, 291
Rathore, 2016, IoT-based smart city development using big data analytical approach, 1
Roy, 2007, A middleware framework for ambiguous context mediation in smart healthcare application
Rudolf, 2013, The graph story of the SAP HANA database, In BTW, 13, 403
Rhipe, 2003. https://www.rhipe.com/ Accessed 30 Dec 2017.
Saidi, 2010, Protein sequences classification by means of feature extraction with substitution matrices, BMC bioinformatics, 11, 175, 10.1186/1471-2105-11-175
Schniederjans, 2013, Enhancing financial performance with social media: An impression management perspective, Decision Support Systems, 55, 911, 10.1016/j.dss.2012.12.027
Science Direct, Digital library. www.sciencedirect.com/ Accessed 30 Dec 2017.
Seddon, 2017, A model for unpacking big data analytics in high-frequency trading, Journal of Business Research, 70, 300, 10.1016/j.jbusres.2016.08.003
Serrato, 2017, The strategic business value of big data, 47
Sezer, 2016, An extended IoT framework with semantics, big data, and analytics, 1849
Sheng, 2017, A multidisciplinary perspective of big data in management research, International Journal of Production Economics, 191, 97, 10.1016/j.ijpe.2017.06.006
Shin, 2016, Demystifying big data: Anatomy of big data developmental process, Telecommunications Policy, 40, 837, 10.1016/j.telpol.2015.03.007
Siddiqa, 2016, A survey of big data management: Taxonomy and state-of-the-art, Journal of Network and Computer Applications, 71, 151, 10.1016/j.jnca.2016.04.008
Siegal, 2010, 683
Simon, 2014
Sivarajah, 2017, Critical analysis of Big Data challenges and analytical methods, Journal of Business Research, 70, 263, 10.1016/j.jbusres.2016.08.001
Sledgianowski, 2017, Toward integration of Big Data, technology and information systems competencies into the accounting curriculum, Journal of Accounting Education, 38, 81, 10.1016/j.jaccedu.2016.12.008
Soman, 2010, A review of wind power and wind speed forecasting methods with different time horizons, 1
Song, H. (2014). Introduction to data visualization: history, concept, methods. https://www.slideshare.net/SookyoungSong/hci-tutorial0212?qid=d736cd0f-b704-4b4f-82ea-7dead9b04e9bandv=andb=andfrom_search=9/ Accessed 24 June 2017.
Sovilj, 2010, OPELM and OPKNN in long-term prediction of time series using projected input data, Neurocomputing, 73, 1976, 10.1016/j.neucom.2009.11.033
Springer, Digital library. http://www.springerlink.com/ Accessed 30 Dec 2017.
Srinivasan, 2013, Leveraging big data analytics to reduce healthcare costs, IT Professional, 15, 21, 10.1109/MITP.2013.55
Srivastava, 1998, Market-based assets and shareholder value: A framework for analysis, The Journal of Marketing, 62, 2, 10.2307/1251799
Strawn, 2012, Scientific research: How many paradigms, Educause Review, 47, 1
Strohbach, 2015, Towards a big data analytics framework for IoT and smart city applications, 257
Sun, 2015, Generalized optimal wavelet decomposing algorithm for big financial data, International Journal of Production Economics, 165, 194, 10.1016/j.ijpe.2014.12.033
Suthaharan, 2014, Big data classification: Problems and challenges in network intrusion prediction with machine learning, ACM SIGMETRICS Performance Evaluation Review, 41, 70, 10.1145/2627534.2627557
Taheri, 2013, A Bee Colony based optimization approach for simultaneous job scheduling and data replication in grid environments, Computers & Operations Research, 40, 1564, 10.1016/j.cor.2011.11.012
Tata Consultancy Services, (2013). The emerging big returns on big data: A TCS 2013 Global Trend Study. http://www.tcs.com/SiteCollectionDocuments/Trends_Study/TCS-Big-Data-Global-Trend-Study-2013.pdf/ Accessed 03 April 2017.
Tavana: Editorial decision analytics, 2014, 1:1. http://www.decisionanalyticsjournal.com/1/1/1/ Accessed 20 Sep 2016.
Tian, 2010, An ensemble ELM based on modified AdaBoost. RT algorithm for predicting the temperature of molten steel in ladle furnace, IEEE Transactions on Automation Science and Engineering, 7, 73, 10.1109/TASE.2008.2005640
Tian, 2015, Latency critical Big data computing in finance, The Journal of Finance and Data Science, 1, 33, 10.1016/j.jfds.2015.07.002
Tkáč, 2016, Artificial neural networks in business: Two decades of research, Applied Soft Computing, 38, 788, 10.1016/j.asoc.2015.09.040
Tolk, 2015, The next generation of modeling & simulation: Integrating big data and deep learning, 1
Tu, 2017, Big data issues in smart grid–A review, Renewable and Sustainable Energy Reviews, 79, 1099, 10.1016/j.rser.2017.05.134
urRehman, 2016, Big data reduction framework for value creation in sustainable enterprises, International Journal of Information Management, 36, 917, 10.1016/j.ijinfomgt.2016.05.013
Vasarhelyi, 2015, Big data in accounting: An overview, Accounting Horizons, 29, 381, 10.2308/acch-51071
Vatrapu, 2016, Social set analysis: A set theoretical approach to big data analytics, IEEE Access, 4, 2542, 10.1109/ACCESS.2016.2559584
Vavpetic, 2013, Semantic data mining of financial news articles, 294
Verhoef, 2016
Villars, 2011, Big data: What it is and why you should care, White Paper, IDC, 14, 1
Vowal Wabbit, Big Data Software. https://en.wikipedia.org/wiki/Vowpal_Wabbit/ Accessed 20 Nov 2017.
Waller, 2013, Data science, predictive analytics, and big data: A revolution that will transform supply chain design and management, Journal of Business Logistics, 34, 77, 10.1111/jbl.12010
Wamba, 2015, How ‘big data'can make big impact: Findings from a systematic review and a longitudinal case study, International Journal of Production Economics, 165, 234, 10.1016/j.ijpe.2014.12.031
Wang, 2016, Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations, Technological Forecasting and Social Change, 126, 3, 10.1016/j.techfore.2015.12.019
Ward, 2014, Applications of business analytics in healthcare, Business horizons, 57, 571, 10.1016/j.bushor.2014.06.003
Weng, 2016, Disease prediction with different types of neural network classifiers, Telematics and Informatics, 33, 277, 10.1016/j.tele.2015.08.006
Wolfert, 2017, Big Data in smart farming–A review, Agricultural Systems, 153, 69, 10.1016/j.agsy.2017.01.023
2014
Wu, 2016
Wu, 2016, The promising future of healthcare services: When big data analytics meets wearable technology, Information & Management, 53, 1020, 10.1016/j.im.2016.07.003
Xie, 2015, Research on big data technology-based agricultural information system, 388
Xing, 2016, Strategies and principles of distributed machine learning on big data, Engineering, 2, 179, 10.1016/J.ENG.2016.02.008
Xu, 2016, The big data analytics and applications of the surveillance system using video structured description technology, Cluster Computing, 19, 1283, 10.1007/s10586-016-0581-x
Yang, 2014, Framework formation of financial data classification standard in the era of the big data, Procedia Computer Science, 30, 88, 10.1016/j.procs.2014.05.385
Yaqoob, 2016, Big data: From beginning to future, International Journal of Information Management, 36, 1231, 10.1016/j.ijinfomgt.2016.07.009
Yazti, 2014, Mobile big data analytics: Research, practice, and opportunities, 1, 1
You, 2013, Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis, BMC Bioinformatics, 14, 1, 10.1186/1471-2105-14-S8-S10
Zhang, 2000, Neural networks for classification: A survey, IEEE Transactions on Systems, Man, and Cybernetics, 30, 451, 10.1109/5326.897072
Zhang, 2015, Data quality, analytics, and privacy in big data, 393
Zhang, 2017, A framework for Big Data driven product lifecycle management, Journal of Cleaner Production, 159, 229, 10.1016/j.jclepro.2017.04.172
Zhao, 2014, Quasi real-time summarization for consumer videos, 2513
Zhao, 2009, Parallel k-means clustering based on mapreduce, 674
Zhao, 2012, A model-based approach for RFID data stream cleansing, 862
Zhou, 2016, Big data driven smart energy management: From big data to big insights, Renewable and Sustainable Energy Reviews, 56, 215, 10.1016/j.rser.2015.11.050
Zhou, 2017, Machine learning on Big Data: Opportunities and challenges, Neurocomputing, 237, 350, 10.1016/j.neucom.2017.01.026
Zikopoulos, 2011