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22nd International Conference on Data Engineering (ICDE'06) (2006)
Atlanta, Georgia
Apr. 3, 2006 to Apr. 7, 2006
ISBN: 0-7695-2570-9
pp: 76
Man Lung Yiu , University of Hong Kong
Nikos Mamoulis , University of Hong Kong
ABSTRACT
Given an object q, modeled by a multidimensional point, a reverse nearest neighbors (RNN) query returns the set of objects in the database that have q as their nearest neighbor. In this paper, we study an interesting generalization of the RNN query, where not all dimensions are considered, but only an ad-hoc subset thereof. The rationale is that (i) the dimensionality might be too high for the result of a regular RNN query to be useful, (ii) missing values may implicitly define a meaningful subspace for RNN retrieval, and (iii) analysts may be interested in the query results only for a set of (ad-hoc) problem dimensions (i.e., object attributes). We consider a suitable storage scheme and develop appropriate algorithms for projected RNN queries, without relying on multidimensional indexes. Our methods are experimentally evaluated with real and synthetic data.
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CITATION

N. Mamoulis and M. L. Yiu, "Reverse Nearest Neighbors Search in Ad-hoc Subspaces," 22nd International Conference on Data Engineering (ICDE'06)(ICDE), Atlanta, Georgia, 2006, pp. 76.
doi:10.1109/ICDE.2006.129
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