SVDPACKC (Version 1.0) User''s Guide
SVDPACKC (Version 1.0) User''s Guide
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Discriminating among word senses using McQuitty's similarity analysis
NAACLstudent '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Proceedings of the HLT-NAACL 2003 student research workshop - Volume 3
Noun sense induction using web search results
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Exploiting context to detect sensitive information in call center conversations
Proceedings of the 17th ACM conference on Information and knowledge management
Discriminating among word meanings by identifying similar contexts
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Vector-Based Unsupervised Word Sense Disambiguation for Large Number of Contexts
TSD '09 Proceedings of the 12th International Conference on Text, Speech and Dialogue
UA-ZSA: web page clustering on the basis of name disambiguation
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
A clustering technique for news articles using WordNet
Knowledge-Based Systems
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SenseClusters is a freely available word sense discrimination system that takes a purely unsupervised clustering approach. It uses no knowledge other than what is available in a raw unstructured corpus, and clusters instances of a given target word based only on their mutual contextual similarities. It is a complete system that provides support for feature selection from large corpora, several different context representation schemes, various clustering algorithms, and evaluation of the discovered clusters.