An Empirical Study of Word Sense Disambiguation

Abstract

Word Sense Disambiguation (WSD) is an important area which has an impact on improving the performance of applications of computational linguistics such as machine translation, information retrieval, text summarization, question answering systems, etc. We have presented a brief history of WSD, discussed the Supervised, Unsupervised, and Knowledge-based approaches for WSD. Though many WSD algorithms exist, we have considered optimal and portable WSD algorithms as most appropriate since they can be embedded easily in applications of computational linguistics. This paper will also provide an idea of some of the WSD algorithms and their performances, which compares and assess the need of the word sense disambiguation. KEYWORDS Supervised, unsupervised, knowledge-based, WordNet, word sense disambiguation