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  • 标题:Integrating Vague Association Mining with Markov Model
  • 本地全文:下载
  • 作者:Priya Bajaj ; Supriya Raheja
  • 期刊名称:International Journal on Soft Computing
  • 电子版ISSN:2229-7103
  • 出版年度:2014
  • 卷号:5
  • 期号:1
  • 页码:1
  • DOI:10.5121/ijsc.2014.5101
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:The increasing demand of World Wide Web raises the need of predicting the user’s web page request. Themost widely used approach to predict the web pages is the pattern discovery process of Web usage mining.This process involves inevitability of many techniques like Markov model, association rules and clustering.Fuzzy theory with different techniques has been introduced for the better results. Our focus is on Markovmodels. This paper is introducing the vague Rules with Markov models for more accuracy using the vagueset theory.
  • 关键词:FUZZY LOGIC; FUZZY MINING APPROACH FOR WEB PAGE PREDICTION;PREDICTION TECHNIQUES; VAGUE;LOGIC;VAGUE ASSOCIATION RULE
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