Distribution-Based Semantic Similarity of Nouns

  • Igor A. Bolshakov
  • Alexander Gelbukh
Conference paper

DOI: 10.1007/978-3-540-76725-1_73

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4756)
Cite this paper as:
Bolshakov I.A., Gelbukh A. (2007) Distribution-Based Semantic Similarity of Nouns. In: Rueda L., Mery D., Kittler J. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2007. Lecture Notes in Computer Science, vol 4756. Springer, Berlin, Heidelberg

Abstract

In our previous work we have proposed two methods for evaluating semantic similarity / dissimilarity of nouns based on their modifier sets registered in Oxford Collocation Dictionary for Student of English. In this paper we provide further details on the experimental support and discussion of these methods. Given two nouns, in the first method the similarity is measured by the relative size of the intersection of the sets of modifiers applicable to both of them. In the second method, the dissimilarity is measured by the difference between the mean values of cohesion between a noun and the two sets of modifiers: its own ones and those of the other noun in question. Here, the cohesion between words is measured via Web statistics for co-occurrences of words. The two proposed measures prove to be in approximately inverse dependency. Our experiments show that Web-based weighting (the second method) gives better results.

Keywords

Semantic relatedness word space model lexical resources Web as corpus natural language processing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Igor A. Bolshakov
    • 1
  • Alexander Gelbukh
    • 1
  1. 1.Center for Computing Research (CIC), National Polytechnic Institute (IPN), Av. Juan Dios Bátiz s/n, Col. Nueva Industrial Vallejo, 07738, Mexico CityMexico

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