A novel access structure for similarity search in metric databases,called Similarity Hashing (SH), is proposed. It is a multi-level hash structure, consisting of search-separable bucket sets on each level. The structure supports easy insertion and bounded search costs, because at most one bucket needs to be accessed at each level for range queries up to a pre-defined value of search radius. At the same time, the pivot-based strategy significantly reduces the number of distance computations. Contrary to tree organizations, the SH structure is suitable for distributed and parallel implementations

Similarity search in metric databases through hashing

Gennaro C;Savino P;
2001

Abstract

A novel access structure for similarity search in metric databases,called Similarity Hashing (SH), is proposed. It is a multi-level hash structure, consisting of search-separable bucket sets on each level. The structure supports easy insertion and bounded search costs, because at most one bucket needs to be accessed at each level for range queries up to a pre-defined value of search radius. At the same time, the pivot-based strategy significantly reduces the number of distance computations. Contrary to tree organizations, the SH structure is suitable for distributed and parallel implementations
2001
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
1-58113-395-2
Access methods
Performance
Metric space
Algorithms
Files
Physical design
Information search and retrieval
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/113974
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