Personalized Search Ranking Based on Semantic Tag

Abstract

The resource getting core of knowledge Service System is the search engine, but the most studies only put attention to improve efficiency, so as to mass resources retrieval results still allows the user to face "cognitive overload" problem when the user to use searcher to get knowledge, how to provide personalized search results become a research focus. This paper provide a new personalized search ranking method, which use semantic tag and user profile to personalized the search results. The experimental results indicate that the method is effective.