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Latent Semantic Analysis Model as a Representation of Free-Association Word Norms

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3 Author(s)
Ortega-Pacheco, D. ; Inst. Politec. Nac., Escuela Super. de Computo, Mexico City, Mexico ; Arias-Trejo, N. ; Martinez, J.B.B.

The current work aims to validate, by means of a computational model, an empirical database of free word association norms of Mexican Spanish. Specifically, this work has two main goals: (1) to detect the associated weight of word word pairs, and (2) to provide an understanding of a lexical network formed beyond an input-output word pair, similar to the mediated priming effect reported experimentally. We used the Term Frequency-Inverse Document Frequency weighting (TFIDF) to obtain the associated weight between an input output word pair and to calculate the TFIDF-Matrix which is used as an input in the Latent Semantic Analysis (LSA) Model. The LSA model is a semantic representation at the lexical level that allows us to understand semantic relationships beyond input-output word pairs. Our computational model replicates and further explains previous experimental work on lexical networks.

Published in:

Artificial Intelligence (MICAI), 2012 11th Mexican International Conference on

Date of Conference:

Oct. 27 2012-Nov. 4 2012

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