Word sense disambiguation and information retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Categorization as probability density estimation
Journal of Mathematical Psychology
Distributional clustering of words for text classification
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Concept decompositions for large sparse text data using clustering
Machine Learning
Placing search in context: the concept revisited
Proceedings of the 10th international conference on World Wide Web
Mixture models of categorization
Journal of Mathematical Psychology
Discovering word senses from text
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Distributional clustering of English words
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Measures of distributional similarity
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Clustering on the Unit Hypersphere using von Mises-Fisher Distributions
The Journal of Machine Learning Research
Improvements in automatic thesaurus extraction
ULA '02 Proceedings of the ACL-02 workshop on Unsupervised lexical acquisition - Volume 9
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
Word Sense Disambiguation: Algorithms and Applications (Text, Speech and Language Technology)
Word Sense Disambiguation: Algorithms and Applications (Text, Speech and Language Technology)
A robust and extensible exemplar-based model of thematic fit
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Cheap and fast---but is it good?: evaluating non-expert annotations for natural language tasks
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A study on similarity and relatedness using distributional and WordNet-based approaches
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Identifying synonyms among distributionally similar words
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Investigations on word senses and word usages
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Random walks for text semantic similarity
TextGraphs-4 Proceedings of the 2009 Workshop on Graph-based Methods for Natural Language Processing
What is word meaning, really?: (and how can distributional models help us describe it?)
GEMS '10 Proceedings of the 2010 Workshop on GEometrical Models of Natural Language Semantics
Measuring distributional similarity in context
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
A mixture model with sharing for lexical semantics
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Exemplar-based word-space model for compositionality detection: shared task system description
DiSCo '11 Proceedings of the Workshop on Distributional Semantics and Compositionality
Evaluating distributional models of semantics for syntactically invariant inference
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
A comparison of models of word meaning in context
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Regular polysemy: a distributional model
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
Improving word representations via global context and multiple word prototypes
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Polarity inducing latent semantic analysis
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Supervised learning of semantic relatedness
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
An inference-based model of word meaning in context as a paraphrase distribution
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction
Clustering memes in social media
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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Current vector-space models of lexical semantics create a single "prototype" vector to represent the meaning of a word. However, due to lexical ambiguity, encoding word meaning with a single vector is problematic. This paper presents a method that uses clustering to produce multiple "sense-specific" vectors for each word. This approach provides a context-dependent vector representation of word meaning that naturally accommodates homonymy and polysemy. Experimental comparisons to human judgements of semantic similarity for both isolated words as well as words in sentential contexts demonstrate the superiority of this approach over both prototype and exemplar based vector-space models.