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The World Wide Web continues to grow at an amazing rate in both the size andcomplexity of Web sites and is well on its way to being the main reservoir ofinformation and data. Due to this increase in growth and complexity of WWW, website publishers are facing increasing difficulty in attracting and retainingusers. To design popular and attractive websites publishers must understandtheir users needs. Therefore analyzing users behaviour is an important part ofweb page design. Web Usage Mining (WUM) is the application of data miningtechniques to web usage log repositories in order to discover the usagepatterns that can be used to analyze the users navigational behavior. WUMcontains three main steps: preprocessing, knowledge extraction and resultsanalysis. The goal of the preprocessing stage in Web usage mining is totransform the raw web log data into a set of user profiles. Each such profilecaptures a sequence or a set of URLs representing a user session.

A Fuzzy Clustering Based Approach for Mining Usage Profiles from Web Log Data