文章基本信息

标题：An Efficient Cluster Based Web Object Filters From Web Pre-Fetching And Web Caching On Web User Navigation
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作者：A. K. Santra ; S. Jayasudha
期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2012
卷号：9
期号：3
出版社：IJCSI Press
摘要：The World Wide Web is a distributed internet system, which provides dynamic and interactive services includes on line tutoring, video/audio conferencing, e-commerce, and etc., which generated heavy demand on network resources and web servers. It increase over the past few year at a very rapidly rate, due to which the amount of traffic over the internet is increasing. As a result, the network performance has now become very slow. Web Pre-fetching and Caching is one of the effective solutions to reduce the web access latency and improve the quality of service. The existing model presented a Cluster based pre-fetching scheme identified clusters of correlated Web pages based on users access patterns. Web Pre-fetching and Caching cause significant improvements on the performance of Web infrastructure. In this paper, we present an efficient Cluster based Web Object Filters from Web Pre-fetching and Web caching scheme to evaluate the web user navigation patterns and user references of product search. Clustering of web page objects obtained from pre-fetched and web cached contents. User Navigation is evaluated from the web cluster objects with similarity retrieval in subsequent user sessions. Web Object Filters are built with the interpretation of the cluster web pages related to the unique users by discarding redundant pages. Ranking is done on users web page product preferences at multiple sessions of each individual user. The performance is measured in terms of Objective function, Number of clusters and cluster accuracy.
关键词：Web usage mining; web mining; web log files; Web Proxy