Paper: JU-Evora: A Graph Based Cross-Level Semantic Similarity Analysis using Discourse Information

ACL ID S14-2064
Title JU-Evora: A Graph Based Cross-Level Semantic Similarity Analysis using Discourse Information
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

Text Analytics using semantic information is the latest trend of research due to its potential to represent better the texts content compared with the bag-of-words approaches. On the contrary, representation of semantics through graphs has several advantages over the tradi- tional representation of feature vector. There- fore, error tolerant graph matching techniques can be used for text comparison. Neverthe- less, not many methodologies exist in the lit- erature which expresses semantic representa- tions through graphs. The present system is designed to deal with cross level semantic similarity analysis as proposed in the SemEval-2014 : Semantic Evaluation, Inter- national Workshop on Semantic Evaluation, Dublin, Ireland.