Web-Page Recommendation Using an Enhanced Incremental Sequence Mining Algorithm Along With Ontology

Web page recommendation is a process to recommend appropriate web pages to the user according to the user interest.When user is on a webpage they should get a proper recommendation so that they gain relevant results. Appropriate knowledge discovery from Web usage data and correct representation of that knowledge for successful Web -page recommendation is important. The paper presents a technique to give better recommendations through semantic enhancement by combining the domain and Web usage data of a website. Here, domain ontologies are used to provide conceptual understanding of a particu lar domain and an incremental mining method,e.g. PLWAP for Update (PL4UP), can be utilized to update web access patterns which are frequent called as (FWAP),which are discovered from the Web usage data. Two important modules are presented.The First is Web Usage Mining which uses the user access sequences which comes from the web logs and gives the most frequent sequences. The second model utilizes ontology to represent the domain knowledge. Also the conceptual prediction model, called as Termnavnet is a navigation network of domain terms and frequent web access patterns is used for supporting Webpage prediction.