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We propose a strategy to perform query processing on P2P similarity search systems based on peers and super-peers. We show that by approximating global but resumed information about the indexed data in each peer, the average amount of computation and communication performed to solve range queries can be significantly reduced as compared to alternative state of the art strategies based on local indexing...
Similarity search has been proved suitable for searching in very large collections of unstructured data objects. We are interested in efficient parallel query processing under situations of continuous streams of queries as in search engines. A number of sequential index data structures for this purpose have been proposed so far. This paper focuses on one representative of a class of these data structures,...
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