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  • 标题:Improving the Efficiency of Bigdata Using Data Mining
  • 本地全文:下载
  • 作者:K.Sudhakar ; M.V.Subbarao ; G.Rajesh
  • 期刊名称:International Journal of Computer Science & Technology
  • 印刷版ISSN:2229-4333
  • 电子版ISSN:0976-8491
  • 出版年度:2015
  • 卷号:6
  • 期号:4
  • 页码:157-164
  • 语种:English
  • 出版社:Ayushmaan Technologies
  • 摘要:Big data is a buzzword, or catch-phrase, used to describe a massive volume of both structured and unstructured data that is so large it is difficult to process using traditional database and software techniques. In most enterprise scenarios the volume of data is too big or it moves too fast or it exceeds current processing capacity. Despite these problems, big data has the potential to help companies improve operations and make faster, more intelligentdecisions.This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This datadriven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations.
  • 关键词:Big Data;Data Mining;Heterogeneity;Autonomous Sources; Complex and Evolving Associations
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