@inproceedings{SisLab3411,
       booktitle = {International Conference on Computational Linguistics and Intelligent Text Processing},
           title = {Hypernymy Detection for Vietnamese Using Dynamic Weighting Neural Network},
          author = {Van Tan Bui and Phuong Thai Nguyen and Van Lam Pham},
            year = {2018},
             url = {https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3411/},
        abstract = {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.}
}