WordNet: a lexical database for English
Communications of the ACM
SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
A systematic comparison of various statistical alignment models
Computational Linguistics
Introduction to the special issue on word sense disambiguation: the state of the art
Computational Linguistics - Special issue on word sense disambiguation
An unsupervised method for word sense tagging using parallel corpora
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Unsupervised Graph-basedWord Sense Disambiguation Using Measures of Word Semantic Similarity
ICSC '07 Proceedings of the International Conference on Semantic Computing
Word sense disambiguation: A survey
ACM Computing Surveys (CSUR)
SemEval-2007 task 17: English lexical sample, SRL and all words
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Improvements to monolingual English word sense disambiguation
DEW '09 Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions
Graph connectivity measures for unsupervised word sense disambiguation
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
COLEUR and COLSLM: A WSD approach to multilingual lexical substitution, tasks 2 and 3 SemEval 2010
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Semantic topic models: combining word distributional statistics and dictionary definitions
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A quick tour of word sense disambiguation, induction and related approaches
SOFSEM'12 Proceedings of the 38th international conference on Current Trends in Theory and Practice of Computer Science
Learning the latent semantics of a concept from its definition
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
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Word Sense Disambiguation remains one of the most complex problems facing computational linguists to date. In this paper we present a system that combines evidence from a monolingual WSD system together with that from a multilingual WSD system to yield state of the art performance on standard All-Words data sets. The monolingual system is based on a modification of the graph based state of the art algorithm In-Degree. The multilingual system is an improvement over an All-Words unsupervised approach, SALAAM. SALAAM exploits multilingual evidence as a means of disambiguation. In this paper, we present modifications to both of the original approaches and then their combination. We finally report the highest results obtained to date on the SENSEVAL 2 standard data set using an unsupervised method, we achieve an overall F measure of 64.58 using a voting scheme.