A cost model for an adaptive cell-based index structure

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Abstract

In this paper, we describe a cost model for an adaptive cell-based index structure which aims at efficient management of immense amounts of spatio-temporal data. We first survey various methods to estimate the performance of R-tree variants. Then, we present our cost model which accurately estimates the number of disk accesses for the adaptive cell-based index structure. To show the accuracy of our model, we perform a detailed analysis using various data sets. The experimental result shows that our model has the average error ratio from 7% to 13%. © Springer-Verlag Berlin Heidelberg 2006.

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Choi, W., Chae, J., Kim, N. J., & Sung, M. Y. (2006). A cost model for an adaptive cell-based index structure. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4263 LNCS, pp. 774–782). Springer Verlag. https://doi.org/10.1007/11902140_81

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