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|Title:||Word sense disambiguation using label propagation based semi-supervised learning||Authors:||Niu, Z.-Y.
|Issue Date:||2005||Citation:||Niu, Z.-Y.,Ji, D.-H.,Tan, C.L. (2005). Word sense disambiguation using label propagation based semi-supervised learning. ACL-05 - 43rd Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference : 395-402. ScholarBank@NUS Repository.||Abstract:||Shortage of manually sense-tagged data is an obstacle to supervised word sense disambiguation methods. In this paper we investigate a label propagation based semisupervised learning algorithm for WSD, which combines labeled and unlabeled data in learning process to fully realize a global consistency assumption: similar examples should have similar labels. Our experimental results on benchmark corpora indicate that it consistently outperforms SVM when only very few labeled examples are available, and its performance is also better than monolingual bootstrapping, and comparable to bilingual bootstrapping. © 2005 Association for Computational Linguistics.||Source Title:||ACL-05 - 43rd Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference||URI:||http://scholarbank.nus.edu.sg/handle/10635/40125||ISBN:||1932432515|
|Appears in Collections:||Staff Publications|
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