Discovering Generalized Association Rule in Web Usage Mining by FP Tree

Abstract

Web mining techniques can use to search for web access patterns, web structures, regularity and dynamics of web contents. Web usage mining analyzes Web log files to discover user accessing patterns of Web pages. Log file data can offer valuable insight into web site usage. It reflects actual usage in natural working condition, compared to the artificial setting of a usability lab. This paper presents web log mining based on hierarchy of web usage data by generalized association rule. Multilevel association rule will be used for implementation of generalized association rule. In this system, Web log database is used to store web log records of log files collected from web server. And web log database are constructed via a process of data cleaning, data transformation. By using FP tree, the system generates rules from web log data, will reduce counting phase of association rule since it stores the pre-computed count values. Frequent patterns are generated instead of page item-sets. The generated frequent patterns can later be applied to improve web site management, decision making process.