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• W1966009082 abstract "Aggregate Nearest Neighbor Queries are much more complex than Nearest Neighbor queries, and pruning strategies are always utilized in ANN queries. Most of the pruning methods are based on the data index mechanisms, such as R-tree. But for the well-known curse of dimensionality, ANN search could be meaningless in high dimensional spaces. In this paper, we propose two non-index pruning strategies in ANN queries on metric space. Our methods utilize the r-NN query and projecting law, analyze the distributing of query points, find out the search region in data space, and get the result efficiently." @default.
• W1966009082 created "2016-06-24" @default.
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• W1966009082 date "2007-06-06" @default.
• W1966009082 modified "2023-09-23" @default.
• W1966009082 title "Finding aggregate nearest neighbor efficiently without indexing" @default.
• W1966009082 cites W2136046112 @default.
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• W1966009082 doi "https://doi.org/10.5555/1366804.1366866" @default.
• W1966009082 hasPublicationYear "2007" @default.
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