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  • 标题:Web Usage Mining: A Fact Finding Approach in Web Mining
  • 本地全文:下载
  • 作者:Rajni Tripathi ; Munesh Chandra Trivedi ; Shraddha Tripathi
  • 期刊名称:International Journal of Computer Trends and Technology
  • 电子版ISSN:2231-2803
  • 出版年度:2014
  • 卷号:12
  • 期号:2
  • 页码:99-103
  • DOI:10.14445/22312803/IJCTT-V12P119
  • 出版社:Seventh Sense Research Group
  • 摘要:Web usage mining is a main research area in Web mining focused on learning about Web users and their interactions with Web sites. The motive of mining is to find users’ access models automatically and quickly from the vast Web log data, such as frequent access paths, frequent access page groups and user clustering. Through web usage mining, the server log, registration information and other relative information left by user access can be mined with the user access mode which will provide foundation for decision making of organizations. This article provides a survey and analysis of current Web usage mining systems and technologies. This paper also discusses an application of WUM, an online Recommender System that dynamically generates links to pages that have not yet been visited by a user and might be of his potential interest. Differently from the recommender systems proposed so far, SUGGEST does not make use of any offline component, and are able to manage Web sites made up of pages dynamically generated.
  • 关键词:User/Session Identification; Web Recommender; Web Log.
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