Determining the Degree of Semantic Similarity Using Prototype Vectors

  • Mireya Tovar
  • David Pinto
  • Azucena Montes
  • Darnes Vilariño
Conference paper

DOI: 10.1007/978-3-642-38989-4_37

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7914)
Cite this paper as:
Tovar M., Pinto D., Montes A., Vilariño D. (2013) Determining the Degree of Semantic Similarity Using Prototype Vectors. In: Carrasco-Ochoa J.A., Martínez-Trinidad J.F., Rodríguez J.S., di Baja G.S. (eds) Pattern Recognition. MCPR 2013. Lecture Notes in Computer Science, vol 7914. Springer, Berlin, Heidelberg

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 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Mireya Tovar
    • 1
    • 2
  • David Pinto
    • 2
  • Azucena Montes
    • 1
    • 3
  • Darnes Vilariño
    • 2
  1. 1.Centro Nacional de Investigación y Desarrollo Tecnológico (CENIDET)Mexico
  2. 2.Faculty Computer ScienceBenemérita Universidad Autónoma de PueblaMexico
  3. 3.Engineering InstituteUniversidad Nacional Autónoma de MexicoMexico

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