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Effective reverse K-nearest neighbor query based on revised R-tree in spatial databases

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3 Author(s)
Boren Li ; School of Earth and Space Sciences, Peking University, Beijing, China ; Mao Pan ; Zixing Wu

This paper presents a novel algorithm for reverse k nearest neighbor queries (RkNN), based on the Revived R*-tree index structure. Existing incremental methods for RkNN have the flowing drawbacks: (i) they cannot support objects in multidimensional space, (ii) their methods are low efficient for incremental query. To solve such RkNN problem efficiently, we propose a novel incremental RkNN algorithm, applied to multidimensional spatial databases. In this algorithm, we introduce a counter for every entry of RR*-tree index structure, which marks the number of nearest neighbor and thus offers the information about the influences of a query point. Experiments analyze synthetic and real data sets and show that our solution is more efficient traditional reverse nearest neighbor queries.

Published in:

Geoinformatics, 2011 19th International Conference on

Date of Conference:

24-26 June 2011