Paper: UMCC_DLSI-(EPS): Paraphrases Detection Based on Semantic Distance

ACL ID S13-2016
Title UMCC_DLSI-(EPS): Paraphrases Detection Based on Semantic Distance
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

This paper describes the specifications and results of UMCC_DLSI-(EPS) system, which participated in the first Evaluating Phrasal Semantics of SemEval-2013. Our supervised system uses different kinds of semantic features to train a bagging classifier used to select the correct similarity option. Related to the different features we can highlight the resource WordNet used to extract semantic relations among words and the use of different algorithms to establish semantic similarities. Our system obtains promising results with a precision value around 78% for the English corpus and 71.84% for the Italian corpus.