DOHNAL, Vlastislav and Pavel ZEZULA. Real-life performance of metric searching. SIGSPATIAL Special. New York, USA: ACM, 2010, vol. 2, No 2, p. 28-31. ISSN 1946-7729.
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Basic information
Original name Real-life performance of metric searching
Authors DOHNAL, Vlastislav (203 Czech Republic, guarantor) and Pavel ZEZULA (203 Czech Republic).
Edition SIGSPATIAL Special, New York, USA, ACM, 2010, 1946-7729.
Other information
Original language English
Type of outcome Article in a journal
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
WWW URL
RIV identification code RIV/00216224:14330/10:00044990
Organization unit Faculty of Informatics
Keywords in English similarity searching; real-life performance; metric space
Tags DISA
Tags International impact, Reviewed
Changed by Changed by: doc. RNDr. Vlastislav Dohnal, Ph.D., učo 2952. Changed: 22/10/2010 16:00.
Abstract
Similarity is a central notion throughout human lives and it will soon become the prevalent strategy for dealing with digital content also in computer systems. But the exponential growth of data makes the scalability and performance issues serious matters of concern. Contemporary decentralized media of mass communication allowing cooperative and collaborative practices enable users autonomously contribute to production of global media, whose elements are in fact related by numerous multi-facet links of similarity. As an example, consider the sites like Flickr, YouTube, or Facebook that host user-contributed heterogeneous content for a variety of events. Accordingly, the core ability of future data processing systems is the similarity management of large and ever growing volumes of data. In a simplified way, the real-life performance can be constrained from two points of view: (1) the query response time, and (2) the query execution throughput, i.e. the number of queries processed per a unit of time.
Abstract (in Czech)
Similarity is a central notion throughout human lives and it will soon become the prevalent strategy for dealing with digital content also in computer systems. But the exponential growth of data makes the scalability and performance issues serious matters of concern. Contemporary decentralized media of mass communication allowing cooperative and collaborative practices enable users autonomously contribute to production of global media, whose elements are in fact related by numerous multi-facet links of similarity. As an example, consider the sites like Flickr, YouTube, or Facebook that host user-contributed heterogeneous content for a variety of events. Accordingly, the core ability of future data processing systems is the similarity management of large and ever growing volumes of data. In a simplified way, the real-life performance can be constrained from two points of view: (1) the query response time, and (2) the query execution throughput, i.e. the number of queries processed per a unit of time.
Links
GA201/09/0683, research and development projectName: Vyhledávání v rozsáhlých multimediálních databázích
Investor: Czech Science Foundation, Similarity Searching in Very Large Multimedia Databases
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