Paper: UPC-CORE: What Can Machine Translation Evaluation Metrics and Wikipedia Do for Estimating Semantic Textual Similarity?

ACL ID S13-1020
Title UPC-CORE: What Can Machine Translation Evaluation Metrics and Wikipedia Do for Estimating Semantic Textual Similarity?
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

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.