JAIST: Clustering and classification based approaches for Japanese WSD

Authors:
Kiyoaki Shirai;Makoto Nakamura
Affiliations:
Japan Advanced Institute of Science and Technology;Japan Advanced Institute of Science and Technology
Venue:
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Year:
2010

Citing 6
Cited 1

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SemEval-2010 task: Japanese WSD

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Word sense disambiguation using heterogeneous language resources

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Word Sense Disambiguation by Combining Labeled Data Expansion and Semi-Supervised Learning Method

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Abstract

This paper reports about our three participating systems in SemEval-2 Japanese WSD task. The first one is a clustering based method, which chooses a sense for, not individual instances, but automatically constructed clusters of instances. The second one is a classification method, which is an ordinary SVM classifier with simple domain adaptation techniques. The last is an ensemble of these two systems. Results of the formal run shows the second system is the best. Its precision is 0.7476.