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. In particular we address the problem of executing the nearest neighbors queries, and propose three different algorithms of query propagation. An extensive experimental study on real-life data sets explores the performance characteristics of the proposed algorithms by showing their advantages and disadvantages.

Erratum to "Nearest neighbor search in metric spaces through Content-Addressable Networks" [Information Processing and Management 43 (2007) 665-683]

Falchi F;Gennaro C;
2008

Abstract

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. In particular we address the problem of executing the nearest neighbors queries, and propose three different algorithms of query propagation. An extensive experimental study on real-life data sets explores the performance characteristics of the proposed algorithms by showing their advantages and disadvantages.
2008
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Algorithms
Design
Experimentation
Measurement
Performance
Theory
Content-Addressable Network
Metric space
Nearest neighbor search
Peer-to-Peer
Similarity search
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/43598
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