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Título del libro: *sem 2013 - 2nd Joint Conference On Lexical And Computational Semantics
Título del capítulo: BUAP: Gram based feature evaluation for the cross-lingual textual entailment task

Autores UNAM:
HELENA MONTSERRAT GOMEZ ADORNO;
Autores externos:

Idioma:

Año de publicación:
2013
Palabras clave:

Classification (of information); Image retrieval; Text processing; Voting machines; Classification models; Cross-lingual; Feature evaluation; Feature vectors; Support vector machine classifiers; Textual entailment; Textual features; Voting systems; Semantics


Resumen:

This paper describes the evaluation of different kinds of textual features for the Cross-Lingual Textual Entailment Task of SemEval 2013. We have counted the number of - grams for three types of textual entities (character, word and PoS tags) that exist in the pair of sentences from which we are interested in determining the judgment of textual entailment. Difference, intersection and distance (Euclidian, Manhattan and Jaccard) of -grams were considered for constructing a feature vector which is further introduced in a support vector machine classifier which allows to construct a classification model. Five different runs were submitted, one of them considering voting system of the previous four approaches. The results obtained show a performance below the median of six teams that have participated in the competition. c 2013 Association for Computational Linguistics


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