Web Usage Pattern Detection Using Cohesive Markov Model with Apriori Algorithm

Web server maintains the essential user log files, recording every request to it. Web log is a record of events which includes all the user details from the time the web visitor initiated the session to the end of the session. The web usage pattern discovery to identify different states of the user access behavior on web. The design of web recommender system using a context-aware Cohesive Markov Model and Apriori clustering is proposed. The prediction rate of proposed algorithm is higher than conventional Markov model.