Paper: LIPN-CORE: Semantic Text Similarity using n-grams, WordNet, Syntactic Analysis, ESA and Information Retrieval based Features

ACL ID S13-1023
Title LIPN-CORE: Semantic Text Similarity using n-grams, WordNet, Syntactic Analysis, ESA and Information Retrieval based Features
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

This paper describes the system used by the LIPN team in the Semantic Textual Similarity task at *SEM 2013. It uses a support vector re- gression model, combining different text sim- ilarity measures that constitute the features. These measures include simple distances like Levenshtein edit distance, cosine, Named En- tities overlap and more complex distances like Explicit Semantic Analysis, WordNet-based similarity, IR-based similarity, and a similar- ity measure based on syntactic dependencies.