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  • 标题:Effective Web personalization system using Modified Fuzzy Possibilistic C Means
  • 本地全文:下载
  • 作者:A. Vaishnavi
  • 期刊名称:Bonfring International Journal of Software Engineering and Soft Computing
  • 印刷版ISSN:2250-1045
  • 电子版ISSN:2277-5099
  • 出版年度:2011
  • 卷号:1
  • 期号:Inaugural Special Issue
  • 页码:01-07
  • DOI:10.9756/BIJSESC.1001
  • 语种:English
  • 出版社:Bonfring
  • 摘要:Due to the rapid growth and development there is an urgent need for the novel technique for the online information system. Web site personalization can be defined as the process of customizing the content and structure of a Web site to the specific and individual needs of each user taking advantage of the user's navigational behavior. A Web personalization system that dynamically suggests interesting URLs for the current user is a major research area of great interest. Clustering plays a very important role in the development of the web personalization. Fuzzy clustering techniques are found to be very efficient in the clustering accuracy. In this paper, a novel technique is proposed for the development of the web personalization system using the Modified Fuzzy Possibilistic C Means (MFPCM). The performance of the proposed Web Personalization system is evaluated based on various parameters. It is observed from the experimental result that the proposed system with MFPCM is effective in providing better and interesting URLs.
  • 关键词:Web Personalization; World Wide Web; MFPCM
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