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• W2904653674 abstract "The lexical entailment recognition problem aims to identify the is-a relation between words. The problem has recently been receiving research attention in the natural language processing field. In this study, we propose a novel method (VLER) for this problem on Vietnamese. For this purpose, we first exploit such lexical structure information of words as a feature, then combine this feature with vectors representation of words such as a unique feature for recognizing the relation. Moreover, we applied a number of methods based on word embedding and supervised learning, experimental results showed that our method achieves the best performance in the hypernymy detection task than other methods in terms of accuracy." @default.
• W2904653674 created "2018-12-22" @default.
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• W2904653674 date "2018-11-01" @default.
• W2904653674 modified "2023-09-27" @default.
• W2904653674 title "Enhancing Performance of Lexical Entailment Recognition for Vietnamese based on Exploiting Lexical Structure Features" @default.
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• W2904653674 doi "https://doi.org/10.1109/kse.2018.8573391" @default.
• W2904653674 hasPublicationYear "2018" @default.
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