Large volumes of data are gathered automatically by Web servers and collected in access log files. Analysis of server access data can provide significant and useful information. Web Usage Mining is the process of applying data mining techniques to the discovery of usage patterns from Web data and is targeted towards applications. It mines the secondary data derived from the interactions of the users during certain period of Web sessions. Web usage mining consists of three phases, namely preprocessing, pattern discovery, and pattern analysis. Given its application potential, Web usage mining has seen a rapid increase in interest, from both the resaerch and practice communities. In this paper, we applied Kohonen's SOM (Self Organizing Map) to pre-processed Web logs of our university Web server logs (http://www.um.ac.ir/) and extract frequent patterns. Result of this paper would be useful for our university Web site owner.

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