Determining the Degree of Semantic Similarity Using Prototype Vectors

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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.

This work is partialy supported by CONACYT and PROMEP under grants: CONACYT 54371, PROMEP/103.5/12/4962 BUAP-792 and project CONACYT 106625.