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Abstract

The results of a full-text, document search by a character string search processor are treated as vector patterns whose elements become a term match grade by use of a membership function of the term match frequency. The closest pattern to the query pattern is found by the similarity between the query pattern and each of the filed sample patterns. The similarity is calculated by use of fuzzy-logic. The similarity is ranked in order of similarity magnitude, thereby reducing the search time. The search time can be shortened by categorizing the filed patterns by term set and similarity to a cluster center pattern. If the cluster center patterns are stored, the closest cluster address can be inferred by fuzzy logic inference from the match between the query document and the term set or the similarity of the query to the cluster center.

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First Claim