Chapter

Pattern Recognition

Volume 7914 of the series Lecture Notes in Computer Science pp 364-373

Determining the Degree of Semantic Similarity Using Prototype Vectors

  • Mireya TovarAffiliated withCarnegie Mellon UniversityCentro Nacional de Investigación y Desarrollo Tecnológico (CENIDET)Faculty Computer Science, Benemérita Universidad Autónoma de Puebla
  • , David PintoAffiliated withCarnegie Mellon UniversityFaculty Computer Science, Benemérita Universidad Autónoma de Puebla
  • , Azucena MontesAffiliated withCarnegie Mellon UniversityCentro Nacional de Investigación y Desarrollo Tecnológico (CENIDET)Engineering Institute, Universidad Nacional Autónoma de Mexico
  • , Darnes VilariñoAffiliated withCarnegie Mellon UniversityFaculty Computer Science, Benemérita Universidad Autónoma de Puebla

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Abstract

Measuring the degree of semantic similarity for word pairs is very challenging task that has been addressed by the computational linguistics community in the recent years. In this paper, we propose a method for evaluating input word pairs in order to measure the degree of semantic similarity. This unsupervised method uses a prototype vector calculated on the basis of word pair representative vectors which are contructed by using snippets automatically gathered from the world wide web.

The obtained results shown that the approach based on prototype vectors outperforms the results reported in the literature for a particular semantic similarity class.

Keywords

Semantic similarity hierarchical relationships prototype vectors