BATKO, Michal, Claudio GENNARO and Pavel ZEZULA. Similarity Grid for Searching in Metric Spaces. In Peer-to-Peer, Grid, and Service-Orientation in Digital Library Architectures: 6th Thematic Workshop of the EU Network of Excellence DELOS. Revised Selected Papers. LNCS 3664. Berlin: Springer-Verlag Heidelberg. p. 25-44. ISBN 3-540-28711-6. 2005.
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Basic information
Original name Similarity Grid for Searching in Metric Spaces
Name in Czech Podobnostní GRID pro hledání v metrických prostrorech
Authors BATKO, Michal (203 Czech Republic), Claudio GENNARO (380 Italy) and Pavel ZEZULA (203 Czech Republic, guarantor).
Edition Berlin, Peer-to-Peer, Grid, and Service-Orientation in Digital Library Architectures: 6th Thematic Workshop of the EU Network of Excellence DELOS. Revised Selected Papers. LNCS 3664, p. 25-44, 20 pp. 2005.
Publisher Springer-Verlag Heidelberg
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 20206 Computer hardware and architecture
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
RIV identification code RIV/00216224:14610/05:00013400
Organization unit Institute of Computer Science
ISBN 3-540-28711-6
UT WoS 000232268700003
Keywords in English distributed data; scalable structures; similarity search; metric space
Tags DISA, distributed data, Metric Space, scalable structures, similarity search
Tags International impact, Reviewed
Changed by Changed by: RNDr. Michal Batko, Ph.D., učo 2907. Changed: 29/6/2009 14:42.
Abstract
Similarity search in metric spaces represents an important paradigm for content-based retrieval of many applications. Existing centralized search structures can speed-up retrieval, but they do not scale up to large volume of data because the response time is linearly increasing with the size of the searched file. The proposed GHT* index is a scalable and distributed structure. By exploiting parallelism in a dynamic network of computers, the GHT* achieves practically constant search time for similarity range queries in data-sets of arbitrary size. The structure also scales well with respect to the growing volume of retrieved data. Moreover, a small amount of replicated routing information on each server increases logarithmically. At the same time, the potential for interquery parallelism is increasing with the growing data-sets because the relative number of servers utilized by individual queries is decreasing. All these properties are verified by experiments on a prototype system using real-life data-sets.
Abstract (in Czech)
Podobnostní hledání v centralizovaném prostředí se ukazuje nedostatečným z hlediska škálovatelnosti. GHT* je distribuovaná struktura pro podobnostní hledání, založeném na metrických prostorech, která dosahuje prakticky konstantní odezvy pro libovolně rozsáhlá data.
Links
1ET100300419, research and development projectName: Inteligentní modely, algoritmy, metody a nástroje pro vytváření sémantického webu
Investor: Academy of Sciences of the Czech Republic, Intelligent Models, Algorithms, Methods and Tools for the Semantic Web (realization)
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