Web Page Prediction Model: Using a Web Usage Mining
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Abstract
Web Usage Mining (WUM) focus on the interaction behavior between web users and requested Web pages in order to identify navigation patterns. A Web page prediction model is use to analyzing the user behavior. Nowadays Web users are facing the problems of information overload and drowning due to the significant and rapid growth in the amount of information and the number of users. As a result, how to provide Web users with more exactly needed information is becoming a critical issue in web-based information retrieval and Web applications. Web data mining is a process that discovers the intrinsic relationships among Web data, which are expressed in the forms of textual, linkage or usage information, via analyzing the features of the Web and web-based data using data mining techniques. This paper concentrate on discovering Web usage pattern via Web usage mining, and then utilize the discovered usage knowledge for presenting Web users with more personalized Web contents to increase the performance of web server.
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Keywords: Web Usage mining, pattern discovery, FAP mining, data cleaning, session construction tree
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