Using Lexical and Thematic Knowledge for Name Disambiguation

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• 作者：Jinpeng Wang (21)
  Wayne Xin Zhao (21)
  Rui Yan (21)
  Haitian Wei (22)
  Jian-Yun Nie (23)
  Xiaoming Li (21)
  
• 关键词：Name Disambiguation ; Lexical and Thematic Knowledge
• 刊名：Lecture Notes in Computer Science
• 出版年：2012
• 出版时间：2012
• 年：2012
• 卷：7675
• 期：1
• 页码：89-102
• 全文大小：249KB
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• 作者单位：Jinpeng Wang (21)
  Wayne Xin Zhao (21)
  Rui Yan (21)
  Haitian Wei (22)
  Jian-Yun Nie (23)
  Xiaoming Li (21)
  
  21. Department of Computer Science and Technology, Peking University, China
  22. School of International Trade and Economics, University of International Business and Economics, China
  23. Dpartement d鈥橧nformatique et de Recherche Oprationnelle, Universit de Montral, Montreal, H3C 3J7, Qubec, Canada
  
• ISSN：1611-3349

文摘

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.