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Efficient User-Adaptable Similarity Search in Large Multimedia Databases

Summary: Introduces user-adaptable similarity search for multimedia databases with quadratic form distance d_A^2(x,y) and A encoding inter-component similarity, enabling ellipsoid queries beyond Euclidean. Index-aware, dimensionality-reduction algorithms support arbitrary A on precomputed indexes, yielding a greatest-lower-bounding similarity with no false drops; C++ implementation tested on 12k histograms. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
8451
Venue
VLDB
Year
1997
Pagerank
0.00010669106
Overall Rank
1,755 | 87.80%
DOI
-

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