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  • 标题:Shift Window FPTree - An Efficient Stream Mining Algorithm
  • 本地全文:下载
  • 作者:Deepak K Mishra ; Varsha Sharma
  • 期刊名称:International Journal of Education and Management Engineering(IJEME)
  • 印刷版ISSN:2305-3623
  • 电子版ISSN:2305-8463
  • 出版年度:2015
  • 卷号:5
  • 期号:4
  • 页码:13-20
  • DOI:10.5815/ijeme.2015.04.02
  • 出版社:MECS Publisher
  • 摘要:Breathless flow in data collection and storage mechanism has enabled Firms to heap up a massive amount of data. In many cases, these huge volumes of data can be mined for fascinating and applicable information in a wide range of applications. When the arrival of data is fast as well in a large bunches in term of amount, this lead major problem to go through this data in both the circumstances in store it and in extracting the useful information from it. To taking under these issues continues mining or stream mining is a best way. Data steam mining allows to not storing the entire data for future prediction which lead to overcome the e-vestige and unnecessary storage overhead. But there is no such way in literature to mine continues data direct, so first one make it feasible accordingly and then mine it. Here in this paper we present an algorithm which handle stream data in very effective manner.
  • 关键词:Data stream mining;flow of data;continues mining
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