LIPN-CORE: Semantic Text Similarity using n-grams, WordNet, Syntactic Analysis, ESA and Information Retrieval based FeaturesReport as inadecuate




LIPN-CORE: Semantic Text Similarity using n-grams, WordNet, Syntactic Analysis, ESA and Information Retrieval based Features - Download this document for free, or read online. Document in PDF available to download.

1 LIPN - Laboratoire d-Informatique de Paris-Nord 2 RCLN LIPN - Laboratoire d-Informatique de Paris-Nord 3 Laboratoire Information, Modèles, Apprentissage Gif-sur-Yvette

Abstract : This paper describes the system used by the LIPN team in the Semantic Textual Similarity task at SemEval 2013. It uses a support vector regression model, combining different text similarity measures that constitute the features. These measures include simple distances like Levenshtein edit distance, cosine, Named Entities overlap and more complex distances like Explicit Semantic Analysis, WordNet-based similarity, IR-based similarity, and a similarity measure based on syntactic dependencies.

Mots-clés : Similarité Sémantique





Author: Davide Buscaldi - Joseph Le Roux - Jorge J. García Flores - Adrian Popescu -

Source: https://hal.archives-ouvertes.fr/



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