Abstract
An important query for spatial database research is to find the closest pair of objects in a given space. Existing work assumes two objects of the closest pair come from two different data sets indexed by R-trees. The closest pair in the whole space will be found via an optimzed R-tree join technique. However, this technique doesn’t perform well when the two data sets are identical. And it doesn’t work when the search range is some area other than the whole space. In this paper, we address the closest pair problem within the same data set. Further more, we propose a practical extension to the closest pair problem to involve a query range. The problem now becomes finding the closest pair of objects among those inside a given range. After extending the existing techniques to solve the new problem, we proposed two index structures based on augmenting the R-tree and we also give algorithms for maintaining these structrures. Experimental results show that our structures are more robust than earlier approaches.
This work was partially supported by NSF grant IIS-0073063.
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Shan, J., Zhang, D., Salzberg, B. (2003). On Spatial-Range Closest-Pair Query. In: Hadzilacos, T., Manolopoulos, Y., Roddick, J., Theodoridis, Y. (eds) Advances in Spatial and Temporal Databases. SSTD 2003. Lecture Notes in Computer Science, vol 2750. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45072-6_15
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DOI: https://doi.org/10.1007/978-3-540-45072-6_15
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