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Discovering Homographs Using N-Partite Graph Clustering

  • Hidekazu Nakawatase
  • Akiko Aizawa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2843)

Abstract

This paper presents a method for discovering homographs from textual corpora. The proposed method first extracts an N-partite graph expression of word dependencies, and then, generates near-synonymous word clusters by enumerating and combining maximum complete sub-components on the graph. The homographs are identified as the words that belong to multiple clusters. In our experiment, we applied the method to Japanese newspaper articles and detected 531 homograph candidates, of which 31 were confirmed to be actual homographs.

Keywords

Bipartite Graph Complete Bipartite Graph Compound Word Word Sense Disambiguation Multiple Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Hattori, S.: Iwanami course philosophy XI language. Iwanami Shoten, Tokyo (1968) (in Japanese)Google Scholar
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    Avis, D., Fukuda, K.: Reverse Search for Enumeration. Discrete Appl. Math. 65, 21–45 (1996)zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Uno, T.: A Practical Fast Algorithm for Finding Clusters of Huge Networks. IPSJ SIGNotes Algorithms No. 088-001. Information Processing Society of Japan, Tokyo (2002) (in Japanese)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Hidekazu Nakawatase
    • 1
  • Akiko Aizawa
    • 2
  1. 1.The Graduate University for advanced studiesTokyoJapan
  2. 2.National Institute of InformaticsTokyoJapan

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