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- Title
一种循环神经网络的词义消歧方法.
- Authors
张春祥; 周雪松; 高雪瑶
- Abstract
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. Target ambiguous word is viewed as center and its four adjacent word units are extracted. Word,part-of-speech and semantic categories are extracted as disambiguation features.Based on disambiguation features, recurrent neural network is used to construct word sense disambiguation classifier. Training corpus in SemEval-2007: Task # 5 and semantic annotation corpus in Harbin Institute of Technology are used to optimize parameters of RNN. Test corpus in SemEval-2007: Task#5 is applied to test word sense disambiguation classifier. Experimental results show that the proposed method can improve accuracy of word sense disambiguation.
- Subjects
AMBIGUITY; SEMANTICS; RECURRENT neural networks; TECHNICAL institutes; NATURAL language processing; CORPORA
- Publication
Journal of Harbin University of Science & Technology, 2020, Vol 25, Issue 1, p80
- ISSN
1007-2683
- Publication type
Article
- DOI
10.15938/j.jhust.2020.01.012