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Building Self-Organized Image Retrieval Network

Basic information
Original title:Building Self-Organized Image Retrieval Network
Authors:Stanislav Bartoň, Vlastislav Dohnal, Jan Sedmidubský, Pavel Zezula
Further information
Citation:BARTOŇ, Stanislav - DOHNAL, Vlastislav - SEDMIDUBSKÝ, Jan - ZEZULA, Pavel. 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. ISBN 978-1-60558-254-2, pp. 51-58. 2008, Napa, CA, USA.
Original language:English
Field:Informatika
Type:Article in Proceedings
Keywords:content-based image retrieval; peer-to-peer network; self-organized system; social networking

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.

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