Knowledge-Based Approach for Word Sense Disambiguation Using Genetic Algorithm for Gujarati

  • Zankhana B. VaishnavEmail author
  • Priti S. Sajja
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 106)


This paper proposes a knowledge-based overlap approach, which uses Genetic algorithms (GAs) for Word Sense Disambiguation (WSD). Genetic Algorithms have been explored to solve search and optimization task in AI. WSD problem strives to resolve which the meaning of a polysemous word should be used in a surrounding context in a given text. Several approaches have been explored for WSD in English, Chinese, Spanish, and also for some Indian regional languages. Despite the extensive research in NLP for Indian Languages, research on WSD in Gujarati Language is very limited. Knowledge-based approach uses machine-readable knowledge source. We propose to use Indo-Aryan WordNet for Gujarati as a lexical database for WSD.


Genetic algorithm Supervised learning Polysemy Semantic network Natural language processing Word sense disambiguation WordNet 


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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Sardar Patel UniversityGujaratIndia
  2. 2.G.H. Patel PG Department of Computer ScienceSardar Patel UniversityGujaratIndia

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