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Word-sense induction a sense of the target word. A well-known approach to context clustering is the Context-group Discrimination algorithm based on large matrix computation methods. Word clustering is a different approach to the induction of word senses. It consists of clustering words, which are semantically similar and can thus bear a specific meaning. Lin’s algorithm is a prototypical example of word clustering, which is based on syntactic dependency statistics, which occur in a corpus to produce sets of words for each discovered sense of a target word. The Clustering By Committee (CBC) also uses syntactic contexts, but exploits a similarity matrix to