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Hypernymy Detection for Vietnamese Using Dynamic Weighting Neural Network

Bui, Van Tan and Nguyen, Phuong Thai and Pham, Van Lam (2018) Hypernymy Detection for Vietnamese Using Dynamic Weighting Neural Network. In: International Conference on Computational Linguistics and Intelligent Text Processing.

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The hypernymy detection problem aims to identify the "is-a" relation between words. The problem has recently been receiving attention from researchers in the field of natural language processing. So far, fairly-effective methods for hypernymy detection in English have been reported. Studies of hypernymy detection in Vietnamese have not been reported yet. In this study, we applied a number of hypernymy detection methods based on word embeddings and supervised learning for Vietnamese. We propose an improvement on the method given by Luu Tuan Anh et al. (2016) by weighting context words proportionally to the semantic similarity between them and the hypernym. Based on Vietnamese WordNet, three datasets for hypernymy detection were built. Experimental results showed that our proposal can increase the efficiency from 8% to 10% in terms of accuracy compared to the original method.

Item Type: Conference or Workshop Item (Paper)
Subjects: Information Technology (IT)
Divisions: Faculty of Information Technology (FIT)
Depositing User: Ngy�n Phương Thái
Date Deposited: 09 Jan 2019 13:53
Last Modified: 09 Jan 2019 13:53

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