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  • 标题:Data Stream Mining – A Survey
  • 本地全文:下载
  • 作者:R. Kalaivani ; Dr. S.Vijayarani
  • 期刊名称:International Journal of Innovative Research in Computer and Communication Engineering
  • 印刷版ISSN:2320-9798
  • 电子版ISSN:2320-9801
  • 出版年度:2017
  • 卷号:5
  • 期号:4
  • 页码:7461
  • DOI:10.15680/IJIRCCE.2017.05040172
  • 出版社:S&S Publications
  • 摘要:At present a growing number of applications that generate massive streams of data which needsintelligent data processing and online analysis. The imminent need for turning such data into useful information andknowledge augments the development of algorithms and frameworks that address streaming challenges. The preprocess, storage space, querying and mining of such data sets are very computationally difficult tasks. Time periodobservation systems, telecommunication methods, sensor devices and alternative dynamic environments are such cases.Mining data streams cares with extracting data structures drawn in model and patterns in continuous streams ofinformation. In this paper, we have a tendency to gift the theoretical foundations of data stream analysis and establishpotential directions of future analysis. Mining data stream techniques are being reviewed.
  • 关键词:Data Stream mining; Data mining; Clustering mining; Classification mining; Association Mining
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