Building Self-Organized Image Retrieval Network

BARTOŇ, Stanislav, Vlastislav DOHNAL, Jan SEDMIDUBSKÝ and Pavel ZEZULA. Building Self-Organized Image Retrieval Network. In Proceeding of the 2008 ACM workshop on Large-Scale distributed systems for information retrieval (LSDS-IR'08). USA: ACM New York, 2008, p. 51-58. ISBN 978-1-60558-254-2.

Basic 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

• Original language: English
• Type of outcome: Proceedings paper
• 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
• 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: content-based image retrieval, DISA, peer-to-peer network, self-organized system, social networking
• Tags: International impact, Reviewed

Abstract

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.

Abstract (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: Name: Distribuované indexační struktury pro podobnostní hledání

Investor: Czech Science Foundation, Distributed Index Structures for Similarity Searching

• 1ET100300419, research and development project: Name: 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)