Abstract
Given a query point q, finding the nearest neighbor (NN) object is one of the most important problem in computer science. In this paper, a bottom-up search algorithm for processing NN query in R-trees is presented. An additional data structure, hash, is introduced to increase the pruning capability of the proposed algorithm. Based on hash, whole data space is disjointly partitioned into n × n cells. Each cell contains the pointers of leaf nodes which intersect with the cell. The experiment shows that the proposed approach outperforms the existing NN search algorithms including the BFS algorithm which is known as I/O optimal algorithm.
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© 2006 Springer-Verlag Berlin Heidelberg
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Song, M., Park, K., Im, S., Kong, KS. (2006). Nearest Neighbor Queries for R-Trees: Why Not Bottom-Up?. In: Li Lee, M., Tan, KL., Wuwongse, V. (eds) Database Systems for Advanced Applications. DASFAA 2006. Lecture Notes in Computer Science, vol 3882. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11733836_68
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DOI: https://doi.org/10.1007/11733836_68
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33337-1
Online ISBN: 978-3-540-33338-8
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