document: Answering relationship queries on the web Finding relationships between entities on the Web , e.g. , the connections between different places or the commonalities of people , is a novel and challenging problem . Existing Web search engines excel in keyword matching and document ranking , but they can not well handle many relationship queries . This paper proposes a new method for answering relationship queries on two entities . Our method first respectively retrieves the top Web pages for either entity from a Web search engine . It then matches these Web pages and generates an ordered list of Web page pairs . Each Web page pair consists of one Web page for either entity . The top ranked Web page pairs are likely to contain the relationships between the two entities . One main challenge in the ranking process is to effectively filter out the large amount of noise in the Web pages without losing much useful information . To achieve this , our method assigns appropriate weights to terms in Web pages and intelligently identifies the potential connecting terms that capture the relationships between the two entities . Only those top potential connecting terms with large weights are used to rank Web page pairs . Finally , the top ranked Web page pairs are presented to the searcher . For each such pair , the query terms and the top potential connecting terms are properly highlighted so that the relationships between the two entities can be easily identified . We implemented a prototype on top of the Google search engine and evaluated it under a wide variety of query scenarios . The experimental results show that our method is effective at finding important relationships with low overhead .
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