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Title:
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UPC-CORE : What can machine translation evaluation metrics and Wikipedia do for estimating semantic textual similarity?
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Author:
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Barrón-Cedeño, Alberto; Màrquez Villodre, Lluís; Fuentes Fort, Maria; Rodríguez Hontoria, Horacio; Turmo Borras, Jorge
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Other authors:
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Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics; Universitat Politècnica de Catalunya. GPLN - Grup de Processament del Llenguatge Natural |
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Abstract:
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In this paper we discuss our participation to
the 2013 Semeval Semantic Textual Similarity
task. Our core features include (i) a set of metrics borrowed from automatic machine translation, originally intended to evaluate automatic 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 translation metrics + explicit semantic analysis and ranked 65 in the competition. Our postcompetition
analysis shows that the features have a good expression level, but overfitting and —mainly— normalization issues caused our correlation values to decrease. |
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Abstract:
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Peer Reviewed |
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Subject(s):
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-Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Llenguatge natural
-Computational linguistics -- Research
-Semantic textual similarity
-Semàntica computacional |
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Rights:
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Document type:
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Article - Draft
Conference Object |
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