Unsupervised document classification using sequential information maximization
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
An empirical evaluation of knowledge sources and learning algorithms for word sense disambiguation
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Resampling Method for Unsupervised Estimation of Cluster Validity
Neural Computation
Word sense disambiguation using label propagation based semi-supervised learning
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Semeval-2007 task 02: evaluating word sense induction and discrimination systems
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Word sense disambiguation: A survey
ACM Computing Surveys (CSUR)
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
An unsupervised aspect-sentiment model for online reviews
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
KCDC: Word sense induction by using grammatical dependencies and sentence phrase structure
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Clustering dictionary definitions using Amazon Mechanical Turk
CSLDAMT '10 Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk
Word sense induction & disambiguation using hierarchical random graphs
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
A part-of-speech lexicographic encoding for an evolutionary word sense disambiguation approach
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part I
Nonparametric Bayesian word sense induction
TextGraphs-6 Proceedings of TextGraphs-6: 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
Evaluating Word Sense Induction and Disambiguation Methods
Language Resources and Evaluation
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This paper describes the implementation of our three systems at SemEval-2007, for task 2 (word sense discrimination), task 5 (Chinese word sense disambiguation), and the first subtask in task 17 (English word sense disambiguation). For task 2, we applied a cluster validation method to estimate the number of senses of a target word in untagged data, and then grouped the instances of this target word into the estimated number of clusters. For both task 5 and task 17, We used the label propagation algorithm as the classifier for sense disambiguation. Our system at task 2 achieved 63.9% F-score under unsupervised evaluation, and 71.9% supervised recall with supervised evaluation. For task 5, our system obtained 71.2% micro-average precision and 74.7% macro-average precision. For the lexical sample subtask for task 17, our system achieved 86.4% coarse-grained precision and recall.