The measurement of semantic relatedness between two words is an important metric for many natural language processing applications. In this paper, we present a novel approach for measuring semantic relatedness that is based on a weighted semantic network. This approach explores the use of a lexicon, semantic relation types as weights, and word definitions as a basis to calculate semantic relatedness. Our results show that our approach outperforms many lexicon-based methods to semantic relatedness, especially on the TOEFL synonym test, achieving an accuracy of 91.25%.
['Reda Siblini', 'Leila Kosseim']
Using a Weighted Semantic Network for Lexical Semantic Relatedness