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Abstract

Disclosed herein is an apparatus and method for similarity searches using hyper-rectangle based multidimensional data segmentation. The similarity search apparatus has MBR generation means, first sequence pruning means, second sequence pruning means, and subsequence finding means. The MBR generation means segments a multidimensional data sequence to be partitioned into subsequences, and represents each subsequence by each Minimum Bounding Rectangle (MBR), such that sets of MBRs are generated from the multidimensional data sequence, and the MBR sets are stored in a database. The first sequence pruning means prunes irrelevant data sequences using a distance D.sub.mbr between MBRs extracted from an inputted query sequence and the MBR sets stored in the database in a multidimensional Euclidean space. The second sequence pruning means prunes irrelevant data sequences using a normalized distance D.sub.norm between MBRs extracted from the query sequence and the MBR sets of data sequences remaining after the data sequences are pruned in a multidimensional Euclidean space. The subsequence finding means detects subsequences similar to the given query sequence by obtaining sets of points contained in MBRs involved in a calculation of the distance D.sub.norm from each sequence obtained using the distance D.sub.norm.

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