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Towards Self-organizing Search Systems

Basic information
Original title:Towards Self-organizing Search Systems
Authors:Stanislav Bartoň, Vlastislav Dohnal, Jan Sedmidubský, Pavel Zezula
Further information
Citation:BARTOŇ, Stanislav - DOHNAL, Vlastislav - SEDMIDUBSKÝ, Jan - ZEZULA, Pavel. Towards Self-organizing Search Systems. In Computational Social Network Analysis. New York, NY, USA : Springer, 2010. Computer Communications and Networks, ISBN 978-1-84882-228-3, pp. 49-80.
Original language:English
Field:Informatika
WWW:link to a new windowhttp://www.springer.com/computer/communications/book/978-1-84882-228-3
Type:Chapter of a book
Keywords:peer-to-peer networking; self-organizing structures; semantic overlay networks; social analysis; content-based information retrieval; metric space; similarity query; experimental evaluation

The huge amount of images, video and music clips produced by various digital devices everyday, must be processed. Firstly, this kind of data calls for content-based search or similarity search rather than keyword-based or text-based search. Secondly, new scalable and efficient methods capable of storing and querying such data must be developed. Although many distributed approaches exist, one of the most suitable and flexible is provided by self-organizing systems. These systems exhibit high resistance to failures in dynamically changing environments. In this chapter, we propose a general three-layer model for designing and implementing a self-organizing system that aims at searching in multimedia data. This model gives a developer guidelines what component must be implemented and how they should behave. The usability of this model is illustrated on a system called Metric Social Network. The architecture of this system is based on the social-network theory that is utilized for establishing links between nodes. The system's properties are verified by organizing and searching in 10 million images.

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