A Personalized Search Results Ranking Method Based on WordNet

Personalized search is more suitable to return search results for user based on different user's search history and improve the search efficiency and user’s retrieval experience. In this paper, we put forward a search results ranking method that uses User Interest Model based on a semantic ontology WordNet, so that it returns the search results in accordance with user interestingness. There into, different types of words are given by different score used different scoring mechanism, in order to obtain user interest model more accurately then provide a basis for measurement for ranking the original search results. The method advanced in this paper is proved to be practical and feasible. It improves the search effect and user’s search experience to some extent.