AMATO, Giuseppe, Pavel ZEZULA, Fausto RABITTI and Pasquale SAVINO. Estimating Proximity of Metric Ball Regions for Multimedia Data Indexing. In Advances in Information Systems. 1st ed. Berlin: Springer, 2000, p. 71-80. LNCS No.1909. ISBN 3-540-4118.
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Basic information
Original name Estimating Proximity of Metric Ball Regions for Multimedia Data Indexing
Authors AMATO, Giuseppe, Pavel ZEZULA, Fausto RABITTI and Pasquale SAVINO.
Edition 1. vyd. Berlin, Advances in Information Systems, p. 71-80, LNCS No.1909, 2000.
Publisher Springer
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10000 1. Natural Sciences
Country of publisher Turkey
Confidentiality degree is not subject to a state or trade secret
RIV identification code RIV/00216224:14330/00:00002644
Organization unit Faculty of Informatics
ISBN 3-540-4118
UT WoS 000174113300007
Changed by Changed by: prof. Ing. Pavel Zezula, CSc., učo 47485. Changed: 19/2/2001 16:58.
Abstract
The problem of defining and computing proximity of regions constraining objects from generic metric spaces is investigated. Approximate, computationally fast, approach is developed for pairs of metric ball regions, which covers the needs of current systems for processing data through distances. The validity and precision of proposed solution is verified by extensive simulation on three substantially different data files. The precision of obtained results is very satisfactory. Besides other possibilities, the proximity measure can be applied to improve the performance of metric trees, developed for multimedia similarity search indexing. Specific system areas concern splitting and merging of regions, pruning regions during similarity retrieval, ranking regions for best case matching, and declustering regions to achieve parallelism.
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