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With the rapid growth of internet technologies, the web has become the world's largest repository of knowledge. So it is challenging task of the webmasters to organize the contents of the particular websites to gather the needs of the users. This paper presents a new framework for a semantic-enhanced Web-page recommendation. This proposed system consists of three models. First two models represent the domain knowledge. The first model shows domain ontology of website. The second model build semantic network of website using domain terms, web pages and relations between them. The third model is personalized meta-search engine, help users to pick up the useful information for them quickly by using their interest keeping in the database. The proposed system automatically discovers and constructs the domain and Web usage knowledge bases, and generate effective Webpage recommendations.

Survey Paper on Website Recommendation System Using Browser History and Domain Knowledge