S-MRST: a novel framework for indexing uncertain data
S-MRST: a novel framework for indexing uncertain data
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S-MRST:一种用于索引不确定数据的新颖框架
DOI:
10.1007/s11280-016-0409-x
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发表时间:
2017-07
影响因子:
3.7
通讯作者:
Wang Guoren
中科院分区:
文献类型:
--
作者:
Zhu Rui;Wang Bin;Luo Shiying;Yang Xiaochun;Wang Guoren
This paper studies the problem of probabilistic range query over uncertain data. Although existing solutions could support such query, it still has space for improvement. In this paper, we firstly propose a novel index called S-MRST for indexing uncertain data. For one thing, via using an irregular shape for bounding uncertain data, it has a stronger space pruning ability. For another, by taking the gradient of probability density function into consideration, S-MRST is also powerful in terms of probability pruning ability. More important, S-MRST is a general index which could support multiple types of probabilistic queries. Theoretical analysis and extensive experimental results demonstrate the effectiveness and efficiency of the proposed index.
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DOI:
10.1109/icde.2002.994710
发表时间:
2002-02
期刊:
Proceedings 18th International Conference on Data Engineering
影响因子:
--
作者:
Anton Faradjian;J. Gehrke;Philippe Bonnet
通讯作者:
Anton Faradjian;J. Gehrke;Philippe Bonnet
DOI:
10.1016/b978-012088469-8.50077-2
发表时间:
2004-08
期刊:
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--
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DOI:
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发表时间:
2011-07
期刊:
Proc. VLDB Endow.
影响因子:
--
作者:
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通讯作者:
T. Bernecker;Tobias Emrich;H. Kriegel;M. Renz;S. Zankl;Andreas Züfle
DOI:
10.1145/1183471.1183504
发表时间:
2006-11
期刊:
--
影响因子:
--
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DOI:
10.1007/978-3-540-71703-4_30
发表时间:
2007-04
期刊:
--
影响因子:
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作者:
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通讯作者:
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