Supervised Word Sense Disambiguation
Abstract: Word Sense Disambiguation (WSD) is the method of the correct sense for word in a context. In this paper we have researched the various approaches for WSD Knowledge based, Supervised, Semi-supervised, Unsupervised methods. This paper has further elaborated on the supervised methods used for WSD. The methods that are compared in this paper are Decision Trees, Decision Lists, Support Vector Machines, Neural Networks, Nave Bayes methods, Exemplar learning.
Keywords: Word Sense Disambiguation, Natural Language Processing, Supervised Learning, Knowledge Acquisition Bottleneck, Sense tagged corpora
How to Cite?: Mihir Sawant, Tanya Sangoi, Sindhu Nair, "Supervised Word Sense Disambiguation", Volume 5 Issue 10, October 2016, International Journal of Science and Research (IJSR), Pages: 1845-1848, https://www.ijsr.net/getabstract.php?paperid=ART20162524, DOI: https://dx.doi.org/10.21275/ART20162524