Making large-scale support vector machine learning practical
Advances in kernel methods
Using LSI for text classification in the presence of background text
Proceedings of the tenth international conference on Information and knowledge management
Transformation-based learning in the fast lane
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
A decision tree of bigrams is an accurate predictor of word sense
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
An empirical study of the domain dependence of supervised word sense disambiguation systems
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
One sense per collocation and genre/topic variations
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
Domain kernels for word sense disambiguation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Domain-specific sense distributions and predominant sense acquisition
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Applying alternating structure optimization to word sense disambiguation
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Domain adaptation with structural correspondence learning
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
SemEval-2007 task 17: English lexical sample, SRL and all words
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
UBC-ALM: combining k-NN with SVD for WSD
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Domain adaptation for statistical classifiers
Journal of Artificial Intelligence Research
Supervised domain adaption for WSD
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
SemEval-2010 task 17: all-words word sense disambiguation on a specific domain
DEW '09 Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions
Knowledge-based WSD on specific domains: performing better than generic supervised WSD
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
SemEval-2010 task: Japanese WSD
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Comparability of LSI and human judgment in text analysis tasks
MMACTEE'09 Proceedings of the 11th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering
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In this paper we explore robustness and domain adaptation issues for Word Sense Disambiguation (WSD) using Singular Value Decomposition (SVD) and unlabeled data. We focus on the semi-supervised domain adaptation scenario, where we train on the source corpus and test on the target corpus, and try to improve results using unlabeled data. Our method yields up to 16.3% error reduction compared to state-of-the-art systems, being the first to report successful semi-supervised domain adaptation. Surprisingly the improvement comes from the use of unlabeled data from the source corpus, and not from the target corpora, meaning that we get robustness rather than domain adaptation. In addition, we study the behavior of our system on the target domain.