2017/08/19 by Reda Siblini, Leila Kosseim, Siblini, Reda +1
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Semantic Web and Ontologies #Topic Modeling #cs.CL
paper · pdf · doi:10.48550/arxiv.1708.05801
In Proceedings of the Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013),June, Atlanta, Georgia, USA, pp. 108-113
arxiv created 2017/08/19 · openalex publication_date 2017/08/19 · arxiv updated 2017/08/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The measurement of phrasal semantic relatedness is an important metric for many natural language processing applications. In this paper, we present three approaches for measuring phrasal semantics, one based on a semantic network model, another on a distributional similarity model, and a hybrid between the two. Our hybrid approach achieved an F-measure of 77.4% on the task of evaluating the semantic similarity of words and compositional phrases.