Resumen de tesis doctoral

Recuperación de Información con Resolución de Ambigüedad de Sentidos de Palabras para el Español

Information Retrieval with Word Sense Disambiguation for Spanish

Graduated: Yoel Ledo Mezquita
Centro de Investigación en Computación (CIC–IPN)
Av. Juan de Dios Bátiz sn esq. Miguel Othón de Mendizábal
C. P. 07738 México D. F.,
e–mail: yledo@yahoo.com

Advisor: Grigori Sidorov
Centro de Investigación en Computación (CIC–IPN)
Av. Juan de Dios Bátiz sn esq. Miguel Othón de Mendizábal
C. P. 07738 México D. F.,
www.cic.ipn.mx/~sidorov

Advisor: Alexander Gelbukh
Centro de Investigación en Computación (CIC–IPN)
Av. Juan de Dios Bátiz sn esq. Miguel Othón de Mendizábal
C. P. 07738 México D. F.,
www.cic.ipn.mx/~sidorov

Graduated on June 23, 2006

Resumen

Uno de los problemas en los portales de recuperación de información en Internet (los portales dinámicos de Altavista, Google, Yahoo, etc.) y en bibliotecas digitales (Biblioteca del Congreso de los EE.UU., etc.) es el de brindar diversas respuestas con muy baja pertinencia. Por ejemplo, un mecánico de autos busca "¿dónde comprar un gato?" y obtiene respuestas sobre los "gatos monteses", "gatos siameses", y otros. Un comerciante de frutas busca "producción de lima" y obtiene respuestas sobre la "ciudad de Lima", "jugo de lima", "lima de uñas", y otros. Estas imprecisiones son debidas a los distintos sentidos que tienen las palabras, lo cual se le conoce como Desambiguación del Sentido de las Palabras (Word Sense Disambiguation, WSD, del inglés.) Este término, es un mecanismo lingüístico para definir el sentido correcto de una palabra, basándose en el contexto donde se emplee, en función de sus posibles sentidos semánticos. Las aportaciones de este artículo consisten en el desarrollo de un nuevo método de desambiguación de sentidos de palabras usando grandes recursos léxicos (diccionarios explicativos, diccionarios de sinónimos, WordNet).

Palabras clave: sentidos de palabras, contexto, diccionarios, algoritmo de Lesk.

Abstract

One of the problems of information retrieval in Internet and digital libraries is low precision: a high number of retrieved documents of low relevance. For example, a person looks for information about jaguars (the animal) and the documents retrieved are about the model of a car. This problem arises due to ambiguity of different senses of words. The task of determining the correct interpretation of a word in its context is known as Word Sense Disambiguation (WSD) task. It employs a linguistic mechanism that detects the most suitable sense of a word, according to the context where the word is used, choosing of its possible senses. In this paper, a new method for word senses disambiguation is proposed based on additional linguistic information for the words in the context available from the large lexical resources, like explanatory dictinary, synonym dictionary, WordNet.

Keywords: word senses, context, dictionaries, Lesk algorithm.

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