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Finding Aggregate Nearest Neighbor Efficiently without Indexing
2007
Proceedings of the 2nd International ICST Conference on Scalable Information Systems
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 wellknown curse of dimensionality, ANN search could be meaningless in high dimensional spaces. In this paper, we propose two nonindex pruning strategies in ANN queries on metric space. Our methods utilize the r-NN query and projecting law, analyze the
doi:10.4108/infoscale.2007.900
dblp:conf/infoscale/LuoFCO07
fatcat:gvqtvmqwgrhoznxpthfjnzdt5a