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https://idr.l3.nitk.ac.in/jspui/handle/123456789/15124
Title: | Word Sense Disambiguation using Bidirectional LSTM |
Authors: | Rakshith J. Savasere S. Ramachandran A. Akhila P. Koolagudi S.G. |
Issue Date: | 2019 |
Citation: | 2019 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2019 - Proceedings , Vol. , , p. - |
Abstract: | Word Sense Disambiguation is considered one of the challenging problems in natural language processing(NLP). LSTM-based Word Sense Disambiguation techniques have been shown effective through experiments. Models have been proposed before that employed LSTM to achieve state-of-the-art results. This paper presents an implementation and analysis of a Bidirectional LSTM model using openly available datasets (Semcor, MASC, SensEval-2 and SensEval-3) and knowledge base (WordNet). Our experiments showed that a similar state of the art results could be obtained with much less data or without external resources like knowledge graphs and parts of speech tagging. © 2019 IEEE. |
URI: | https://doi.org/10.1109/DISCOVER47552.2019.9008031 http://idr.nitk.ac.in/jspui/handle/123456789/15124 |
Appears in Collections: | 2. Conference Papers |
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