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A Sentence-to-Sentence Clustering Procedure for Pattern Analysis

Cluster analysis for patterns represented by sentences is investigated. The similarity between patterns is expressed in terms of the distance between their corresponding sentences. A weighted distance between two strings is defined and its probabilistic interpretation given. The class membership of an input pattern (sentence) is determined according to the nearest neighbor or k-nearest neighbor rule. A clustering procedure on a sentence-to-sentence basis is proposed. A set of English characters is used to illustrate the proposed metric and clustering procedure.