UPC-CORE : What can machine translation evaluation metrics and Wikipedia do for estimating semantic textual similarity?
Document typeConference lecture
Defense date2013
Rights accessOpen Access
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Abstract
CitationBarron-Cedeño, A. [et al.]. UPC-CORE : What can machine translation evaluation metrics and Wikipedia do for estimating semantic textual similarity?. A: Joint Conference on Lexical and Computational Semantics. "*SEM 2013: The Second Joint Conference on Lexical and Computational Semantics". Atlanta: 2013, p. 1-5.
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| 60_Paper.pdf | In this paper we discuss our participation to the 2013 Semeval Semantic Textual Similarity task. Our core features include (i) a set of met- rics borrowed from automatic machine trans- lation, originally intended to evaluate auto- matic against reference translations and (ii) an instance of explicit semantic analysis, built upon opening paragraphs of Wikipedia 2010 articles. Our similarity estimator relies on a support vector regressor with RBF kernel. Our best approach required 13 machine transla- tion metrics + explicit semantic analysis and ranked 65 in the competition. Our post- competition analysis shows that the features have a good expression level, but overfitting and —mainly— normalization issues caused our correlation values to decrease. | 57,80Kb | View/Open |