Detailed Information on Publication Record
2008
Building Self-Organized Image Retrieval Network
BARTOŇ, Stanislav, Vlastislav DOHNAL, Jan SEDMIDUBSKÝ and Pavel ZEZULABasic information
Original name
Building Self-Organized Image Retrieval Network
Name in Czech
Building Self-Organized Image Retrieval Network
Authors
BARTOŇ, Stanislav (203 Czech Republic, guarantor), Vlastislav DOHNAL (203 Czech Republic), Jan SEDMIDUBSKÝ (203 Czech Republic) and Pavel ZEZULA (203 Czech Republic)
Edition
USA, Proceeding of the 2008 ACM workshop on Large-Scale distributed systems for information retrieval (LSDS-IR'08), p. 51-58, 8 pp. 2008
Publisher
ACM New York
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
RIV identification code
RIV/00216224:14330/08:00024257
Organization unit
Faculty of Informatics
ISBN
978-1-60558-254-2
Keywords in English
content-based image retrieval; peer-to-peer network; self-organized system; social networking
Tags
Tags
International impact, Reviewed
Změněno: 12/11/2008 13:24, RNDr. Stanislav Bartoň, Ph.D.
V originále
We propose a self-organized content-based Image Retrieval Network (IRN) that is inspired by a Metric Social Network (MSN) search system. The proposed network model is strictly data-owner oriented so no data redistribution among peers is needed in order to efficiently process queries. Thus a shared database where each peer is fully in charge of its data, is created. The self-organization of the network is obtained by exploiting the social-network approach of the MSN -- the connections between peers in the network are created as social-network relationships formed on the basis of a query-answer principle. The knowledge of answers to previous queries is used to fast navigate to peers, possibly containing the best answers to new queries. Additionally, the network uses a randomized mechanism to explore new and unvisited parts of the network. In this way, the self-adaptability and robustness of the system are achieved. The proposed concepts are verified using a real network consisting of 2,000 peers containing descriptive features of 10 million images from the Flickr Photo Sharing system.
In Czech
We propose a self-organized content-based Image Retrieval Network (IRN) that is inspired by a Metric Social Network (MSN) search system. The proposed network model is strictly data-owner oriented so no data redistribution among peers is needed in order to efficiently process queries. Thus a shared database where each peer is fully in charge of its data, is created. The self-organization of the network is obtained by exploiting the social-network approach of the MSN -- the connections between peers in the network are created as social-network relationships formed on the basis of a query-answer principle. The knowledge of answers to previous queries is used to fast navigate to peers, possibly containing the best answers to new queries. Additionally, the network uses a randomized mechanism to explore new and unvisited parts of the network. In this way, the self-adaptability and robustness of the system are achieved. The proposed concepts are verified using a real network consisting of 2,000 peers containing descriptive features of 10 million images from the Flickr Photo Sharing system.
Links
| GP201/07/P240, research and development project |
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| 1ET100300419, research and development project |
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