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The only information left behind by many users visiting a Web site is the path through the pages they have accessed. Most of the Web information retrieval tools only use the textual information, while ignore the link information that could be very valuable.

Web usage mining, the application of data mining techniques to discover user navigation patterns from web data, tries to discovery the useful information from the secondary data derived from the interactions of the users while surfing on the Web. It focuses on the techniques that could predict user behavior while the user interacts with Web.

M. Spiliopolou [Spilio 1999] abstract the potential strategic aims in each domain into mining goal as: prediction of the user's behavior within the site, comparison between expected and actual Web site usage, adjustment of the Web site to the interests of its users. There are no definite distinctions between the Web usage mining and other two categories. In the process of data preparation of Web usage mining, the Web content and Web site topology will be used as the information sources, which interacts Web usage mining with the Web content mining and Web structure mining. Moreover, the clustering in the process of pattern discovery is a bridge to Web content and structure mining from usage mining.

There are lots of works have been done in the Information Retrieval, Database, Intelligent Agents and Topology, which provide a sound foundation for the Web content mining, Web structure mining. Web usage mining is a relative new research area, and gains more and more attentions in recent years.