Discovery the User Access Pattern from Web Log Based on Association Rule Mining

Abstract

Nowadays , most of the people who may be in educational field, IT fiel d, or business field or others widely use the internet. The e learning, e mailing, eCommerce and other online techniques are used. The usage data are recorded by the Web server as the Web Log Data. Web usage mining mines Web Log Data to discover user acces s patterns of Web page. Association Rules are used to discover the user access patterns. So, in this paper, the Support ordered Trie Itemset (SOTrieIT) algorithm to analyze which is the most frequent visited website and Apriori algorithm, which is candidat e generation algorithm to know the pairs of websites, are used. From the result of this paper, user can analyze the websites' popularity, usefulness and effectiveness. Web administration can use this system for finding the appropriate actions.