Apriori algorithm on web logs for mining frequent link

Abstract

Web mining is a combination of data mining and World Wide Web. It consists of three types namely web structure mining, web content mining and web usage mining. Web Usage Mining is one of the parts of web mining and extracts the web users' behavior from web log file. This paper consists of three phases. The first one is data preprocessing phase, which is the most important one because it makes the data with good quality. This can be done by data cleaning, user identification, and session identification. The next one is pattern discovery phase; in this the users' navigational pattern and rules are extracted by using apriori algorithm. Final one is pattern analysis phase, which is used to analyze and visualize the rules. The aim of this paper is to identify the frequent link from web log data by using the Apriori algorithm.