doi:10.3850/978-981-08-7300-4_0141

ABSTRACT

This paper focuses for the field of web usage mining framework to track the user session in a dynamic websites. This paper will track all the users from login time to logout time. The main feature of our paper is, this is a complete framework and findings in mining web usage patterns from web log files of a real web site that has all the difficult aspects of real-life web usage mining, including developing user profiles and external data describing an ontology of the web content. The web log files normally maintained in user side but in our proposed system we are going to maintain in servers. So also we can track the website profiles. Also we can analyze the traffics in the client side by using this paper. The survey results are clustered and given to the client side servers not in web servers. Which are the links are mostly used by the user. An objective validation plan is also used to assess the quality of the mined profiles, in particular their adaptability in the face of evolving user behavior. The user session traces all reported to the server using the clustering technique by the user web logs.

Keywords: Clustering methods, Traffic measurement, Web traffic characterization, Web session traces.

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