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Word Sense Disambiguation System for Information Retrieval in Telugu Language

Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 292)


Nowadays, In Natural Language Processing (NLP), using artificial intelligence is a open challenge. Word Sense Disambiguation (WSD) is a sub field of artificial intelligence. In this research paper, WSD system is developed and validated for regional Telugu language. Many Natural Languages are having many ambiguous words. The word having more than one sense is known as ambiguous word or polysemy word. Word Sense Disambiguation is termed as the methodology of finding the appropriate sense of the ambiguity word. To develop WSD system a training dataset Lexical Knowledge Base LKB is used. In Query Expansion, WSD technique is used to increase the accuracy of the information retrieval system. In this research paper, baseline method and the proposed method Word First Sense are discussed. The evaluation metrics used are Normalized Discounted Cumulative Gain (NDCG) and Mean Average Precision (MAP) metrics. The results are encouraging in the proposed method.


  • WSD
  • NLP
  • Query expansion
  • MAP
  • NDCG
  • Artificial intelligence

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I sincerely thank the principal and management of MLR Institute of Technology for providing me the facilities Laboratory and Internet WI-FI. I also thank all the authors in my reference section which helped me a lot in framing this research article.

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Koppula, N., Pradeep Kumar, J., Srinivas Rao, K., Kiran Kumar, G. (2022). Word Sense Disambiguation System for Information Retrieval in Telugu Language. In: Mandal, J.K., De, D. (eds) Advanced Techniques for IoT Applications. EAIT 2021. Lecture Notes in Networks and Systems, vol 292. Springer, Singapore.

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