Results 11 to 20 of about 31,258 (204)
Supervised Learning and Knowledge-Based Approaches Applied to Biomedical Word Sense Disambiguation [PDF]
Journal of Integrative Bioinformatics, 2017 Word sense disambiguation (WSD) is an important step in biomedical text mining, which is responsible for assigning an unequivocal concept to an ambiguous term, improving the accuracy of biomedical information extraction systems.
Antunes Rui, Matos Sérgio
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Chinese Word Sense Disambiguation using a LSTM [PDF]
ITM Web of Conferences, 2017 Word sense disambiguation (WSD) is a challenging natural language processing (NLP) problem. We propose a new strategy for WSD, which at first replaces the interesting word in a sentence by the different synonyms corresponding to the different meanings ...
Sun Xue-Ren +3 more
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Word sense disambiguation for event trigger word detection in biomedicine [PDF]
BMC Bioinformatics, 2011 This paper describes a method for detecting event trigger words in biomedical text based on a word sense disambiguation (WSD) approach. We first investigate the applicability of existing WSD techniques to trigger word disambiguation in the BioNLP 2009 ...
Martinez David, Baldwin Timothy
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Knowledge-based biomedical word sense disambiguation: comparison of approaches [PDF]
BMC Bioinformatics, 2010 Background Word sense disambiguation (WSD) algorithms attempt to select the proper sense of ambiguous terms in text. Resources like the UMLS provide a reference thesaurus to be used to annotate the biomedical literature.
Aronson Alan R, Jimeno-Yepes Antonio J
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Word Sense Disambiguation Using Clustered Sense Labels
Applied Sciences, 2022 Sequence labeling models for word sense disambiguation have proven highly effective when the sense vocabulary is compressed based on the thesaurus hierarchy.
Jeong Yeon Park +2 more
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Efficient estimation of Hindi WSD with distributed word representation in vector space
Journal of King Saud University: Computer and Information Sciences, 2022 Word Sense Disambiguation (WSD) is significant for improving the accuracy of the interpretation of a Natural language text. Various supervised learning-based models and knowledge-based models have been developed in the literature for WSD of the language ...
Archana Kumari, D.K. Lobiyal
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Role of Genetic Algorithm in Optimization of Hindi Word Sense Disambiguation
IEEE Access, 2022 The Word Sense Disambiguation system is widely used in many fields, including business, research, education, and government organizations. The availability of natural language data on the internet has grown in tandem with the rapid advancement of ...
Surbhi Bhatia +2 more
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A Method of Word Sense Disambiguation with Recurrent Netural Networks
Journal of Harbin University of Science and Technology, 2020 Word sense disambiguation is an important research problem in natural language processing field. For the phenomenon that a Chinese word has many senses, recurrent neural network (RNN) is used to determine true meaning of ambiguous word with its context ...
ZHANG Chunxiang +2 more
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Determining the difficulty of Word Sense Disambiguation [PDF]
Journal of Biomedical Informatics, 2014 Automatic processing of biomedical documents is made difficult by the fact that many of the terms they contain are ambiguous. Word Sense Disambiguation (WSD) systems attempt to resolve these ambiguities and identify the correct meaning. However, the published literature on WSD systems for biomedical documents report considerable differences in ...
McInnes, Bridget T., Stevenson, Mark
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Chinese Word Sense Disambiguation Based on Word translation and Part of speech
Journal of Harbin University of Science and Technology, 2020 For vocabulary ambiguity problem in Chinese, CNN (Convolution Neural Network) is adopted to determine true meaning of ambiguous vocabulary where word, part of speech and translation around its left and right adjacent words are used.
ZHANG Chunxiang +2 more
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