Kyungsun Kim
2018
Word Sense Disambiguation Based on Word Similarity Calculation Using Word Vector Representation from a Knowledge-based Graph
Dongsuk O
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Sunjae Kwon
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Kyungsun Kim
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Youngjoong Ko
Proceedings of the 27th International Conference on Computational Linguistics
Word sense disambiguation (WSD) is the task to determine the word sense according to its context. Many existing WSD studies have been using an external knowledge-based unsupervised approach because it has fewer word set constraints than supervised approaches requiring training data. In this paper, we propose a new WSD method to generate the context of an ambiguous word by using similarities between an ambiguous word and words in the input document. In addition, to leverage our WSD method, we further propose a new word similarity calculation method based on the semantic network structure of BabelNet. We evaluate the proposed methods on the SemEval-13 and SemEval-15 for English WSD dataset. Experimental results demonstrate that the proposed WSD method significantly improves the baseline WSD method. Furthermore, our WSD system outperforms the state-of-the-art WSD systems in the Semeval-13 dataset. Finally, it has higher performance than the state-of-the-art unsupervised knowledge-based WSD system in the average performance of both datasets.
2005
Improving Korean Speech Acts Analysis by Using Shrinkage and Discourse Stack
Kyungsun Kim
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Youngjoong Ko
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Jungyun Seo
Second International Joint Conference on Natural Language Processing: Full Papers
2001
MAYA: A Fast Question-answering System Based on a Predictive Answer Indexer
Harksoo Kim
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Kyungsun Kim
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Gary Geunbae Lee
|
Jungyun Seo
Proceedings of the ACL 2001 Workshop on Open-Domain Question Answering
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Co-authors
- Jungyun Seo 2
- Youngjoong Ko 2
- Harksoo Kim 1
- Gary Geunbae Lee 1
- Dongsuk O 1
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