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Volume & Issue no: Volume 3, Issue 7, July 2014


Analysis of Web Usage Mining
Author Name:
Swarna Latha Ampilli, Suresh Tippana
ABSTRACT With the growing popularity of the World Wide Web (Web), large volumes of data are gathered automatically by Web servers and collected in access log files. Analysis of server access data can provide significant and useful information. The web is an important source of information retrieval nowadays, and the users accessing the web are from different backgrounds. The usage information about users are recorded in web logs. Analyzing web log files to extract useful patterns is called web usage mining. Web usage mining approaches include clustering, association rule mining, sequential pattern mining etc.To facilitates web page access by users, and web recommendation model is needed.Web Usage Mining (WUM) integrates the techniques of two popular research fields - Data Mining and the Internet. By analyzing the potential rules hidden in web logs, WUM helps personalize the delivery of web content and improve web design, customer satisfaction and user navigation through pre-fetching and caching. Keywords— web usage mining, web mining, pre-processing, pattern discovery, pattern analysis.
Cite this article:
Swarna Latha Ampilli, Suresh Tippana , " Analysis of Web Usage Mining" , International Journal of Application or Innovation in Engineering & Management (IJAIEM) , Volume 3, Issue 7, July 2014 , pp. 013-019 , ISSN 2319 - 4847.
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