An associative method for Lesk-based word sense disambiguation
Sulema Torres-Ramos, Israel Román-Godínez, Gerardo Mendizabal‐Ruiz · Americanae (AECID Library) · 2017
Abstract One of the most important current problems in natural language processing is word sense disambiguation (WSD). WSD consists of identifying the correct sense of the words in a given text. In this work, we present a novel method for automatic WSD based on the simplified-Lesk algorithm. The proposed method employs Alpha-Beta associative memories for the relatedness computation between the senses of the ambiguous words and its context. The performance of this method was evaluated in terms of precision, recall, and F-score, using the semantically annotated corpora Senseval-2, Semcor, and Semeval-2007. The results show the advantages of the proposed method compared with other Lesk-based state-of-the-art methods.