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In this paper, an unsupervised semantic class induction algorithm is proposed that is based on the principle that similarity of context implies similarity of meaning. Two semantic similarity metrics that are variations of the vector product distance are used in order to measure the semantic distance between words and to automatically generate semantic classes. The first metric computes "wide-context"...
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