In this paper, we target on the problem of personal name disambiguation in search results returned by personal name queries. Usually, a personal name refers to several people. Therefore, when a search engine returns a set of documents containing that name, they are often relevant to several individuals with the same namesake. Automatic differentiation of people in the resulting documents may help users to search for the person of interest easier. We propose a method that uses web directories to improve the similarity measurement in personal name disambiguation. We carried out experiments on real web documents in which we compared our method with the vector space model method and the named entity recognition method. The results show that our method has advantages over these previous methods.
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