Discovering the Association Rules in Data Cube from Web Server Log Files

Abstract

Analyzing and exploring regularities in the behavior of the web page reader is imprinted on the web server log files can improve system performance; enhance the quality and delivery of Internet information services to the end user.Web mining techniques can use to search for web access patterns, web structures, regularity and dynamics of web contents. OLAP (Online Analytical Processing)-based association rule mining integrates OLAP and association rule mining that facilitates flexible mining of interesting knowledge in data cube because it can be performed at multilevel or multidimensional in data cube.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. Data cube will be implemented from log files.Generating rules from data cube will reduce counting phase of association rule since it stores the pre-computed count values.Frequent patterns are generated based on dimensions of the web logs instead of page itemsets. The generated frequent patterns can later be applied to improve web site management, decision making process.