Exploiting concept network-based user profile for personalized web search: A re-ranking approach

This paper proposes a novel way of personalized web search through re-ranking search results with user profiles of concept-network structure. Basically, personalized search systems need to be based upon user profiles that contain usert search patterns, with which they expand initial queries or re-rank the search results. The proposed method is a sort of a re-ranking personalized search method integrated with query expansion facility. The method identifies some documents which occur commonly among a set of different search results retrieved from expanded queries, and re-ranks the search results in terms of the degree of co-occurring. We show that the proposed method outperforms the conventional ones by performing the empirical web search with a number of actual users who have diverse information needs and query intents.