SenseClusters — Finding Clusters that Represent Word Senses

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.

Authors

• Amruta Purandare
• Ted Pedersen Richard Maclin

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