2008
Building Self-Organized Image Retrieval Network
BARTOŇ, Stanislav, Vlastislav DOHNAL, Jan SEDMIDUBSKÝ a Pavel ZEZULAZákladní údaje
Originální název
Building Self-Organized Image Retrieval Network
Název česky
Building Self-Organized Image Retrieval Network
Autoři
BARTOŇ, Stanislav (203 Česká republika, garant), Vlastislav DOHNAL (203 Česká republika), Jan SEDMIDUBSKÝ (203 Česká republika) a Pavel ZEZULA (203 Česká republika)
Vydání
USA, Proceeding of the 2008 ACM workshop on Large-Scale distributed systems for information retrieval (LSDS-IR'08), od s. 51-58, 8 s. 2008
Nakladatel
ACM New York
Další údaje
Jazyk
angličtina
Typ výsledku
Stať ve sborníku
Obor
10201 Computer sciences, information science, bioinformatics
Stát vydavatele
Spojené státy
Utajení
není předmětem státního či obchodního tajemství
Kód RIV
RIV/00216224:14330/08:00024257
Organizační jednotka
Fakulta informatiky
ISBN
978-1-60558-254-2
Klíčová slova anglicky
content-based image retrieval; peer-to-peer network; self-organized system; social networking
Štítky
Příznaky
Mezinárodní význam, Recenzováno
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.
Česky
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.
Návaznosti
| GP201/07/P240, projekt VaV |
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| 1ET100300419, projekt VaV |
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