ABSTRACT

Web usage mining is the application of web mining to discover the useful patterns from the web in order to understand and analyze the behavior of the web users and web based applications. It is the emerging research trend for today’s researchers. It entirely deals with web log files which contain the user website access information. It is an interesting thing to analyze and understand the user behavior about the web access. Web usage mining normally has three categories: 1. Preprocessing, 2. Pattern Discovery and 3. Pattern Analysis. This paper proposes the association rule mining algorithms for better Web Recommendation and Web Personalization. Web recommendation systems are considered as an important role to understand customers’ behavior, interest, improving customer convenience, increasing service provider profits and future needs.