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Using Lexical and Thematic Knowledge for Name Disambiguation

  • Jinpeng Wang
  • Wayne Xin Zhao
  • Rui Yan
  • Haitian Wei
  • Jian-Yun Nie
  • Xiaoming Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7675)

Abstract

In this paper we present a novel approach to disambiguate names based on two different types of semantic information: lexical and thematic. We propose to use translation-based language models to resolve the synonymy problem in every word match, and to use topic-based ranking function to capture rich thematic contexts for names. We test three ranking functions that combine lexical relatedness and thematic relatedness. The experiments on Wikipedia data set and TAC-KBP 2010 data set show that our proposed method is very effective for name disambiguation.

Keywords

Name Disambiguation Lexical and Thematic Knowledge 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jinpeng Wang
    • 1
  • Wayne Xin Zhao
    • 1
  • Rui Yan
    • 1
  • Haitian Wei
    • 2
  • Jian-Yun Nie
    • 3
  • Xiaoming Li
    • 1
  1. 1.Department of Computer Science and TechnologyPeking UniversityChina
  2. 2.School of International Trade and EconomicsUniversity of International Business and EconomicsChina
  3. 3.Dpartement d’Informatique et de Recherche OprationnelleUniversit de MontralMontrealCanada

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