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  • 标题:Efficient Text Mining using Improved IPE Algorithm
  • 本地全文:下载
  • 作者:Alfiya Sana ; Prateek Gupta
  • 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:2017
  • 卷号:8
  • 期号:2
  • 页码:151-154
  • 语种:English
  • 出版社:Ayushmaan Technologies
  • 摘要:Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Over the years, people have often held the hypothesis that pattern (or phrase)- based approaches should perform better than the term-based ones, but many experiments do not support this hypothesis. This paper presents an innovative and effective pattern discovery technique which includes the processes of pattern deploying and pattern evolving, to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information. For achieving the relevant output which is left due to less frequency, improved IPE has been suggested and proposed to be implemented in this work.
  • 关键词:Data Mining;Inner Pattern Evaluation;Association Rule Mining; Threshold Based Mining;Pattern Deploying;Pattern Evolving
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