Discovering corpus-specific word senses
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
Word Sense Induction Using Graphs of Collocations
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
The role of named entities in web people search
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
The S-Space package: an open source package for word space models
ACLDemos '10 Proceedings of the ACL 2010 System Demonstrations
SemEval-2010 task 14: Word sense induction & disambiguation
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Word sense induction & disambiguation using hierarchical random graphs
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
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
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Word Sense Induction (WSI) is an unsupervised approach for learning the multiple senses of a word. Graph-based approaches to WSI frequently represent word co-occurrence as a graph and use the statistical properties of the graph to identify the senses. We reinterpret graph-based WSI as community detection, a well studied problem in network science. The relations in the co-occurrence graph give rise to word communities, which distinguish senses. Our results show competitive performance on the SemEval-2010 WSI Task.