Masaki Ikeda

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The more important web searching becomes, the more we have to focus on the " same name " problem in web searches. In this paper, we report our algorithm for disambiguating person names in web search results. It is a document clustering algorithm based on hierarchical agglomerative clustering using named entities, compound keywords, and URLs as features for(More)
In this paper, we report our system that disambiguates person names in Web search results. The system uses named entities, compound key words, and URLs as features for document similarity calculation, which typically show high precision but low recall clustering results. We propose to use a two-stage clustering algorithm by bootstrapping to improve the low(More)
The more important the web search become, the bigger the same name problem in the web search. Proposed solution is forming clusters of people from search results. In this paper, we report our algorithms that disambiguates person names in web search results. Our clustering algorithm is based on hierarchical agglomerative clustering using named entities,(More)
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