Unsupervised word sense discrimination relies on the idea that words that occur in similar contexts will have similar meanings. These techniques cluster multiple contexts in which an ambiguous word occurs, and the number of clusters discovered indicates the number of senses in which the ambiguous word is used. One important distinction among these methods is the underlying means of representing the contexts to be clustered. This paper compares the efficacy of first