Nearest neighbor search in metric spaces through Content-Addressable Networks

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Authors	FALCHI Fabrizio GENNARO Claudio ZEZULA Pavel
Year of publication	2007
Type	Article in Periodical
Magazine / Source	Information Processing and Management
MU Faculty or unit	Faculty of Informatics
Citation
web	http://www.sciencedirect.com/science/journal/03064573
Field	Informatics
Keywords	similarity search; scalability; peer-to-peer architecture; nearest neigbor; content addressing
Description	Most of the peer-to-peer search techniques proposed in the recent years have focused on the single-key retrieval. However, similarity search in metric spaces represents an important paradigm for content-based retrieval in many applications. In this paper we introduce an extension of the well-known Content-Addressable Network paradigm to support storage and retrieval of more generic metric space objects.
Related projects:	Intelligent Models, Algorithms, Methods and Tools for the Semantic Web (realization)