Building a web-scale image similarity search system
Multimedia Tools and Applications
Empirical evaluation of excluded middle vantage point forest on biological sequences workload
Proceedings of the 1st Workshop on New Trends in Similarity Search
Metric-Based similarity search in unstructured peer-to-peer systems
Transactions on Large-Scale Data- and Knowledge-Centered Systems V
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Due to the exponential growth of digital data and its complexity, we need a technique which allows us to search such collections efficiently. A suitable solution seems to be based on the peer-to-peer (P2P) network paradigm and the metric-space model of similarity. During the building phase of the distributed structure, the peers often split as new peers join the network. During a peer split, the local data is halved and one half is migrated to the new peer. In this paper, we study the problem of efficient splits of metric data locally organized by an M-tree and we propose a novel algorithm for speeding the splits up. In particular, we focus on the metric-based structured P2P network called the M-Chord. In experimental evaluation, we compare the proposed algorithm with several straightforward solutions on a real network organizing 10 million images. Our algorithm provides a significant performance boost.