WordNet: a lexical database for English
Communications of the ACM
Discovering word senses from text
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Word Sense Induction Using Graphs of Collocations
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Two graph-based algorithms for state-of-the-art WSD
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Automatic identification of non-compositional multi-word expressions using latent semantic analysis
MWE '06 Proceedings of the Workshop on Multiword Expressions: Identifying and Exploiting Underlying Properties
Semeval-2007 task 02: evaluating word sense induction and discrimination systems
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
TextGraphs-1 Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing
Word sense induction for novel sense detection
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
An evaluation of graded sense disambiguation using word sense induction
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
Evaluating Word Sense Induction and Disambiguation Methods
Language Resources and Evaluation
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This paper presents an unsupervised graph-based method for automatic word sense induction and disambiguation. The innovative part of our method is the assignment of either a word or a word pair to each vertex of the constructed graph. Word senses are induced by clustering the constructed graph. In the disambiguation stage, each induced cluster is scored according to the number of its vertices found in the context of the target word. Our system participated in SemEval-2010 word sense induction and disambiguation task.