TY - GEN
T1 - Efficient evaluation of partially-dimensional range queries using adaptive R*-tree
AU - Feng, Yaokai
AU - Makinouchi, Akifumi
PY - 2006
Y1 - 2006
N2 - This paper is about how to efficiently evaluate partially-dimensional range queries, which are often used in many actual applications. If the existing multidimensional indices are employed to evaluate partially-dimensional range queries, then a great deal of information that is irrelevant to the queries also has to be read from disk. A modification of R*-tree is described in this paper to ameliorate such a situation. Discussions and experiments indicate that the proposed modification can clearly improve the performance of partially-dimensional range queries, especially for large datasets.
AB - This paper is about how to efficiently evaluate partially-dimensional range queries, which are often used in many actual applications. If the existing multidimensional indices are employed to evaluate partially-dimensional range queries, then a great deal of information that is irrelevant to the queries also has to be read from disk. A modification of R*-tree is described in this paper to ameliorate such a situation. Discussions and experiments indicate that the proposed modification can clearly improve the performance of partially-dimensional range queries, especially for large datasets.
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M3 - Conference contribution
AN - SCOPUS:33749415024
SN - 3540378715
SN - 9783540378716
VL - 4080 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 687
EP - 696
BT - Database and Expert Systems Applications - 17th International Conference, DEXA 2006, Proceedings
PB - Springer Verlag
T2 - 17th International Conference on Database and Expert Systems Applications, DEXA 2006
Y2 - 4 September 2006 through 8 September 2006
ER -