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
doaj +1 more source
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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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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Word Sense Disambiguation Based on RegNet With Efficient Channel Attention and Dilated Convolution
IEEE Access, 2023 Word sense disambiguation (WSD) is one of key problems in field of natural language processing. Ambiguous word often has different meanings in different contexts.
Chun-Xiang Zhang +2 more
doaj +1 more source
Multi-Head Self-Attention Gated-Dilated Convolutional Neural Network for Word Sense Disambiguation
IEEE Access, 2023 Word sense disambiguation (WSD) is to determine correct sense of ambiguous word based on its context. WSD is widely used in text classification, machine translation and information retrieval and so on.
Chun-Xiang Zhang +2 more
doaj +1 more source
Multi-feature Word Sense Disambiguation Based on Dependency Parsing Analysis [PDF]
Jisuanji gongcheng, 2017 Word Sense Disambiguation(WSD) plays an important role in machine translation,information retrieval and speech semantic recognition.In order to improve the quality of disambiguation and refine the feature,a multi-feature granularity WSD scheme is ...
SHI Zhaopeng,ZOU Xuxi,XIANG Runzhao
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Word shape analysis for a hybrid recognition system [PDF]
, 2003 This paper describes two wholistic recognizers developed for use in a hybrid recognition system. The recognizers use information about the word shape. This information is strongly related to word zoning.
Powalka, RK, Sherkat, N, Whitrow, RJ
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Unsupervised, Knowledge-Free, and Interpretable Word Sense Disambiguation [PDF]
, 2017 Interpretability of a predictive model is a powerful feature that gains the trust of users in the correctness of the predictions. In word sense disambiguation (WSD), knowledge-based systems tend to be much more interpretable than knowledge-free ...
Biemann, Chris +6 more
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3D Model Classification Based on GCN and SVM
IEEE Access, 2022 3D model classification is an important task. Now, 3D model is usually expressed as point cloud. Disorder of point cloud brings great difficulty into 3D model classification.
Xue-Yao Gao +2 more
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Name Disambiguation from link data in a collaboration graph using temporal and topological features [PDF]
, 2015 In a social community, multiple persons may share the same name, phone number or some other identifying attributes. This, along with other phenomena, such as name abbreviation, name misspelling, and human error leads to erroneous aggregation of records ...
Hasan, Mohammad Al +2 more
core +2 more sources