BATKO, Michal, David NOVÁK, Fabrizio FALCHI and Pavel ZEZULA. Scalability Comparison of Peer-to-Peer Similarity Search Structures. Future Generation Computer Systems. Amsterdam, The Netherlands: Elsevier Science, 2008, vol. 24, No 8, p. 834-848. ISSN 0167-739X.
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Basic information
Original name Scalability Comparison of Peer-to-Peer Similarity Search Structures
Name in Czech Porovnání škálovatelnosti peer-to-peer struktur pro podobnostní vyhledávání
Authors BATKO, Michal (203 Czech Republic, belonging to the institution), David NOVÁK (203 Czech Republic, guarantor, belonging to the institution), Fabrizio FALCHI (380 Italy) and Pavel ZEZULA (203 Czech Republic, belonging to the institution).
Edition Future Generation Computer Systems, Amsterdam, The Netherlands, Elsevier Science, 2008, 0167-739X.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Netherlands
Confidentiality degree is not subject to a state or trade secret
WWW DOI identifier of the paper
Impact factor Impact factor: 1.476
RIV identification code RIV/00216224:14330/08:00024131
Organization unit Faculty of Informatics
UT WoS 000258426100008
Keywords in English Similarity search; Scalability; Metric space; Distributed index structures; Peer-to-Peer networks
Tags DISA, Distributed index structures, Metric Space, Peer-to-Peer Networks, scalability, similarity search
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 30/4/2015 16:20.
Abstract
Due to the increasing complexity of current digital data, similarity search has become a fundamental computational task in many applications. Unfortunately, its costs are still high and grow linearly on single server structures, which prevents them from efficient application on large data volumes. In this paper, we shortly describe four recent scalable distributed techniques for similarity search and study their performance in executing queries on three different datasets. Though all the methods employ parallelism to speed up query execution, different advantages for different objectives have been identified by experiments. The reported results would be helpful for choosing the best implementations for specific applications. They can also be used for designing new and better indexing structures in the future.
Abstract (in Czech)
Kvůli rostoucí složitosti současných digitálních dat se stalo podobnostní vyhledávání základním výpočetním úkolem v mnoha aplikacích. V tomto článku krátce popisujeme čtyři škálovatelné distribuované techniky pro podobnostní vyhledávání a studujeme jejich výkon při vyhodnocování dotazů na různých datových množinách.
Links
GD102/05/H050, research and development projectName: Integrovaný přístup k výchově studentů DSP v oblasti paralelních a distribuovaných systémů
Investor: Czech Science Foundation, Integrated approach to education of PhD students in the area of parallel and distributed systems
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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