WordNet-based Collaborative Weighting for Ranking Web Pages

H. Kim, K. Yu, and J. Kim (Korea)


Intelligent Information System, Search Engine, WordNet,


In this paper we propose a new ranking method for Web search engine. As the majority of current search engines use keyword-based method for similarity computing, they cannot discriminates important Web pages among huge amount of search results. The proposed system reflects collaborative evaluation by users by accumulating the number of clicks on a Web page. The number of click is stored separately according to the semantic category of the query words that is determined by using the WordNet. Experiments with several keywords show that the accuracy of search can be improved by using the sense-specific collaborative weighting.

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