Indirect Positive and Negative Association Rules in Web Usage Mining

Abstract

One of the purposes of Web usage mining is to find out interesting user association rules from web server logs. It has become vital for personalization, effective web site management, business and support services, creating adaptive web sites, and so on. In the web domain, items correspond to pages and transactions to user sessions. Indirect associations, type of infrequent pattern provide useful insight into the data. The concept of indirect association is to indirectly connect two rarely co-occurred pages via a third page called transitive page. Mining positive and negative association rules in web usage data become a hot spot. So, these all information leads find new approach for discovering efficient rules for web. Indirect positive and Negative Association Rules are discussed here which can be used for Web Recommendation, personalization etc. Mining indirect positive and negative association rules for the web is explored very little so far in the research work. The presented Proposed Approach of algorithm is to extract the positive and negative association rules from web session log file and then discover the indirect positive and negative association rules from it.