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

Abstract

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 traditional representation of feature vector. Therefore, error tolerant graph matching techniques can be used for text comparison. Nevertheless, not many methodologies exist in the literature which expresses semantic representations through graphs. The present system is designed to deal with cross level semantic similarity analysis as proposed in the SemEval-2014 : Semantic Evaluation, International Workshop on Semantic Evaluation, Dublin, Ireland.