北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2006, Vol. 29 ›› Issue (s2): 96-100.doi: 10.13190/jbupt.2006s2.96.311

• 论文 • 上一篇    下一篇

语义网络结构下的词义消歧

王菁华1,刘建毅1,2,王枞1   

  1. 1. 北京邮电大学 信息工程学院, 北京 100876; 2. 北京师范大学 中文信息处理研究所, 北京 100875
  • 收稿日期:2006-09-12 修回日期:1900-01-01 出版日期:2006-11-30 发布日期:2006-11-30
  • 通讯作者: 王菁华

Word Sense Disambiguation with Semantic Graph Structure

WANG Jing-hua1, LIU Jian-yi1,2, WANG Cong1   

  1. 1. School of Information Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China; 2. Graduate School of Chinese Information Processing, Beijing Normal University, Beijing 100875, China)
  • Received:2006-09-12 Revised:1900-01-01 Online:2006-11-30 Published:2006-11-30
  • Contact: WANG Jing-hua

摘要:

提出了一种基于语义网络结构的词义消歧方法。将文本片段中出现词的所有词义都看作节点,将两个词的任意两个词义之间的语义关系看作弧,将语义关系的紧密程度看作弧的权重,从而构成一个无向赋权网络;将Google的网页分级(PageRank)算法应用到无向赋权图中,评价网络中节点的重要性,并结合共指词义和词义的常用程度,对文本中出现的名词进行消歧。实验证明了该方法对文本进行词义消歧是有效的。

关键词: 词义消歧, 语义网络, 词网, 网页分级算法

Abstract:

A word sense disambiguation method based on semantic graph structure was presented. In the method, a text is represented as an undirected weighted semantic graph with WordNet, which defines synsets as vertices and relations of vertices as edges, and assigns the weight of edges with the relatedness of connected synsets. Combining with coherence synset and the synset frequency, PageRank* which is a modified PageRank formula for undirected weighted graph, was used to disambiguate the nouns in the text. The experimental result shows that this method is effective and practical.

Key words: word sense disambiguation, semantic graph, WordNet, PageRank

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