With nurturing reputation of the World Wide Web, large quantity of web usage data is collected by the web servers and stored in web access log files. Web usage mining is a technology to mine valuable knowledge from the World Wide Web. It intends to discover interesting user access patterns from web log files. Analysis of these user access patterns is used to determine that the information architecture of the web site can be reorganized to better facilitate information retrieval. Association rule mining is also used to find association relationships amongst large data sets. Mining frequent sequential patterns is a significant aspect in association rule mining. Based on this, the changes can be suggested to the web site by placing embedded hyperlinks on the home page to the frequently accessed sections of the web site. In this paper, a very efficient algorithm has been adopted for expert systems to mine frequent sequential patterns in web usage data

Data Mining, Web Mining, Association rule mining, Frequent sequential pattern mining, Web Log files, Web usage

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