Using a knowledge base to disambiguate personal name in web search results

  • Authors:

  • Quang Minh Vu;Tomonari Masada;Atsuhiro Takasu;Jun Adachi

  • Affiliations:

  • The University of Tokyo, Tokyo, Japan;National Institute of Information, Tokyo, Japan;National Institute of Information, Tokyo, Japan;National Institute of Information, Tokyo, Japan

  • Venue:
  • Proceedings of the 2007 ACM symposium on Applied computing
  • Year:
  • 2007

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Abstract

Results of queries by personal names often contain documents related to several people because of the namesake problem. In order to differentiate documents related to different people, an effective method is needed to measure document similarities and to find documents related to the same person. Some previous researchers have used the vector space model or have tried to extract common named entities for measuring similarities. We propose a new method that uses Web directories as a knowledge base to find shared contexts in document pairs and uses the measurement of shared contexts to determine similarities between document pairs. Experimental results show that our proposed method outperforms the vector space model method and the named entity recognition method.