Results 61 to 70 of about 83,244 (255)
Attention Neural Network for Biomedical Word Sense Disambiguation
Discrete Dynamics in Nature and Society, 2022 In order to improve the disambiguation accuracy of biomedical words, this paper proposes a disambiguation method based on the attention neural network. The biomedical word is viewed as the center. Morphology, part of speech, and semantic information from
Chun-Xiang Zhang +4 more
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Word sense disambiguation and information retrieval [PDF]
, 1994 It has often been thought that word sense ambiguity is a cause of poor performance in Information Retrieval (IR) systems. The belief is that if ambiguous words can be correctly disambiguated, IR performance will increase.
Sanderson, M.
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Retrieving with good sense [PDF]
, 2000 Although always present in text, word sense ambiguity only recently became regarded as a problem to information retrieval which was potentially solvable.
Sanderson, M.
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A Corpus-Based Word Sense Disambiguation For Geez Language
Ethiopian Journal of Science and Sustainable Development, 2021 In natural language processing, languages have a number of ambiguous words and solving such kind of problem for the language can help the development of word sense disambiguation using corpusbased Approach.
Amlakie Aschale Alemu, Kinde Anlay Fante
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WORD SENSE DISAMBIGUATION FOR TAMIL LANGUAGE USING PART-OF-SPEECH AND CLUSTERING TECHNIQUE [PDF]
Journal of Engineering Science and Technology, 2017 Word sense disambiguation is an important task in Natural Language Processing (NLP), and this paper concentrates on the problem of target word selection in machine translation.
P. ISWARYA, V. RADHA
doaj
Memory-based word sense disambiguation
Computers and the humanities, 1999 We describe a memory-based classification architecture for word sense disambiguation and its application to the SENSEVAL evaluation task. For each ambiguous word, a semantic word expert is automatically trained using a memory-based approach. In each expert, selecting the correct sense of a word in a new context is achieved by finding the closest match ...
Veenstra, J. +4 more
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SensEmBERT: Context-Enhanced Sense Embeddings for Multilingual Word Sense Disambiguation
AAAI Conference on Artificial Intelligence, 2020 Contextual representations of words derived by neural language models have proven to effectively encode the subtle distinctions that might occur between different meanings of the same word.
Bianca Scarlini +2 more
semanticscholar +1 more source
Improving Data Integration through Disambiguation Techniques [PDF]
, 2008 In this paper Word Sense Disambiguation (WSD) issue in the context of data integration is outlined and an Approximate Word Sense Disambiguation approach (AWSD) is proposed for the automatic lexical annotation of structured and semi-structured data ...
PO, Laura
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Biomedical Word Sense Disambiguation Based on Graph Attention Networks
IEEE Access, 2022 Biomedical words have many semantics. Biomedical word sense disambiguation (WSD) is an important research issue in biomedicine field. Biomedical WSD refers to the process of determining meanings of ambiguous word according to its context.
Chun-Xiang Zhang +2 more
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A word sense disambiguation corpus for Urdu [PDF]
Language Resources and Evaluation, 2018 The aim of word sense disambiguation (WSD) is to correctly identify the meaning of a word in context. All natural languages exhibit word sense ambiguities and these are often hard to resolve automatically. Consequently WSD is considered an important problem in natural language processing (NLP).
Saeed, A. +3 more
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