Comprehensive Method of Knowledge-Based Approach for Word-Sense Disambiguation

  • Pornima GidheEmail author
  • Leena Ragha
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 34)


We share our knowledge, thoughts, and information on the Web through our Natural Language (NL). Most of the words in NL are ambiguous and change the meaning of a sentence. Humans can disambiguate the meaning through perceived intelligence, but it is challenging task for a system. Many researchers are working on Word-Sense Disambiguation (WSD) which is used to get correct sense out of context to make the sense of a text understandable by machine/application. We focus on Knowledge-Based (KB) approaches which rely on knowledge resource like WordNet. We compared KB algorithms such as Lesk, Walker, and Conceptual Density with the help of common dataset of sentences. Comparative analysis is done to find the limitations of individual algorithms based on the analysis; we propose a comprehensive method of KB approach.


Knowledge based Word-sense disambiguation (WSD) Natural language processing (NLP) 


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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Computer Engineering DepartmentRAIT MumbaiMumbaiIndia

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