International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 115

Review Papers | Computer Science & Engineering | India | Volume 4 Issue 2, February 2015


Supervised, Semi-Supervised and Unsupervised WSD Approaches: An Overview

Lokesh Nandanwar | Kalyani Mamulkar


Abstract: Word Sense Disambiguation (WSD) involves the identification of a correct sense of a word in a given sentence. WSD is considered to be an open and AI-complete problem of Natural Language Processing (NLP). WSD is found to be most important in many applications like Machine translation (MT), Information retrieval (IR), Information extraction (IE), text mining, and Lexicography. Supervised, Semi-supervised and Unsupervised Approaches to WSD are found to be important and very successful learning approaches. These methods are categorized based on the main source of knowledge used to differentiate senses or type and amount of annotated (labeled) corpora (data) required. Semi-supervised approach requires lesser quantity of annotated corpora as compared to supervised approaches which needs large amount of annotated corpora while unsupervised approach uses unannotated (unlabeled) corpora for training. In this paper, we will discuss all the three approaches and their respective methods in details


Keywords: Word Sense Disambiguation, Natural language processing, Supervised approach, Semi-supervised approach, unsupervised approach


Edition: Volume 4 Issue 2, February 2015,


Pages: 1684 - 1688


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How to Cite this Article?

Lokesh Nandanwar, Kalyani Mamulkar, "Supervised, Semi-Supervised and Unsupervised WSD Approaches: An Overview", International Journal of Science and Research (IJSR), Volume 4 Issue 2, February 2015, pp. 1684-1688, https://www.ijsr.net/get_abstract.php?paper_id=SUB151598

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