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  • 标题:A Survey on Data Stream and Its Various Techniques
  • 本地全文:下载
  • 作者:Hiral Desai ; Dharmik Vasiyani ; Jay Gandhi
  • 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:2015
  • 卷号:3
  • 期号:9
  • DOI:10.15680/IJIRCCE.2015. 0309090
  • 出版社:S&S Publications
  • 摘要:Data StreamMining is become new emerging topic for research in knowledge discovery. In thiscontinuous changing nature of data creates problem in mining the knowledge from it and its difficult to store. There aresome techniques and algorithms which are using for mining in the data stream like classification, clustering andfrequent patterns. Here gives an overview of all these techniques with their merits and demerits.There are mainly fourchallenges termed as Concept drift, Infinite length, Concept evaluation and Limited labeled data. Here also givesdescription of all these challenges.With reference to all these problem here gives discussion of future work
  • 关键词:data stream; concept drift; concept evolution; infinite length; limited labeled data
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