Fuzzy Possibilistic C-Means Algorithm for Clustering on Web Usage Mining to Predict the User Behavior
Web usage mining is the major application of data mining approach to learn usage patterns from web data, with the intention of enhanced understanding and serve the requirements of web-based applications. It is the major application of data mining techniques to web log data repositories. Web usage mining includes three most important steps: data preprocessing, knowledge extraction and analysis of extracted results. Knowledge extraction step is used in finding the user access patterns from web access log. Clustering is one of the typical algorithms in the field of data mining. The main objective of this paper is to organize a website into a set of clusters, which consists of "Similar" data items based on the user behavior and navigation patterns.