Web Page Recommendation Using Key Information Extraction and PREWAP

Web page recommendation is the technique of web site customization required by individual user or group of users. The web page recommendation system exploits the patterns of the web pages visited by users. Our proposed system is oriented towards improves performance of a web page recommendation system with minimum time computation and memory usage achieved by using various models; the first model is Web Usage Mining which utilizes the web logs. The second model also utilizes web logs to represent the domain knowledge, here the domain ontology is used to solve the new page problem. Extracting key terms from the generated ontology, use of redundant ontological information reduced using Key Information Extraction Algorithm. Also implements PREWAP algorithm which gives better results than existing PLWAP for updated dataset. Likewise, the prediction model, which is a network of domain terms, which is based on the frequently viewed web-pages and represents the integrated web usage. The recommendation results have been successfully verified based on the results which are acquired from a proposed and existing web usage mining (WUM) technique.