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
The design, implementation, and use of the Ngram statistics package
CICLing'03 Proceedings of the 4th international conference on Computational linguistics and intelligent text processing
Of mice and terms: clustering algorithms on ambiguous terms in folksonomies
Proceedings of the 2010 ACM Symposium on Applied Computing
Evaluating Word Sense Induction and Disambiguation Methods
Language Resources and Evaluation
| Hi-index | 0.00 |
SenseClusters is a freely available word sense discrimination system that takes a purely unsu-pervised 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.