NOVÁK, David and Michal BATKO. Metric Index: An Efficient and Scalable Solution for Similarity Search. In Proceedings of the 2009 Second International Workshop on Similarity Search and Applications. Washington, DC, USA: IEEE Computer Society, 2009. p. 65-73, 9 pp. ISBN 978-0-7695-3765-8.
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Basic information
Original name Metric Index: An Efficient and Scalable Solution for Similarity Search
Name in Czech Metrický index: Efektivní a Škálovatelné řešení pro podobnostní vyhledávání
Authors NOVÁK, David (203 Czechia, guarantor, belonging to the institution) and Michal BATKO (203 Czechia, belonging to the institution).
Edition Washington, DC, USA, Proceedings of the 2009 Second International Workshop on Similarity Search and Applications, p. 65-73, 9 pp. 2009.
Publisher IEEE Computer Society
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
WWW ACM Portal Link
RIV identification code RIV/00216224:14330/09:00029661
Organization unit Faculty of Informatics
ISBN 978-0-7695-3765-8
UT WoS 000282087600008
Keywords in English metric space; similarity search; data structure; approximation; scalability
Tags DISA
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 14/3/2016 14:48.
Abstract
Metric space as a universal and versatile model of similarity can be applied in various areas of non-text information retrieval. However, a general, efficient and scalable solution for metric data management is still a resisting research challenge. We introduce a novel indexing and searching mechanism called Metric Index (M-Index), that employs practically all known principles of metric space partitioning, pruning and filtering. The heart of the M-Index is a general mapping mechanism that enables to actually store the data in well-established structures such as the B+-tree or even in a distributed storage. We have implemented the M-Index with B+-tree and performed experiments on a combination of five MPEG-7 descriptors in a database of hundreds of thousands digital images. The experiments put under test several M-Index variants and compare them with two orthogonal approaches - the PM-Tree and the iDistance. The trials show that the M-Index outperforms the others in terms of efficiency of search-space pruning, I/O costs, and response times for precise similarity queries. Furthermore, the M-Index demonstrates an excellent ability to keep similar data close in the index which makes its approximation algorithm very efficient - maintaining practically constant response times while preserving a very high recall as the dataset grows.
Abstract (in Czech)
Metrický prostor je univerzálním modelem podobnosti, který může být použit v různých oblastech netextového vyhledávání. Představujeme nový indexační a vyhledávácí mechanismus s názvem "Metric Index" (M-Index), který využívá prakticky všechny známé principy dělení, prořezávání a filtrování metrického prostoru. Experimenty ukazují, že M-Index poráží ostatní struktury v efektivitě omezování vyhledávácího prostoru, nákladech na V/V a době odezvy pro přesné podobnostní vyhledávání. Navíc M-Index prokazuje vyjimečnou schopnost držet podobná data blízko u sebe, což velmi zefektivňuje jeho aproximační algoritmus - dosahuje téměř konstantní doby odezvy pro rostoucí velikost databáze přičemž udržuje vysokou kvalitu odpovědi.
Links
GA201/09/0683, research and development projectName: Vyhledávání v rozsáhlých multimediálních databázích
Investor: Czech Science Foundation, Standard Projects
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