DocumentCode :
2851913
Title :
Compression of OLAP Cubes for Aggregate Queries Based on Copula Approach
Author :
Gao, Yazhuo ; Ni, Zhiwei ; Ni, Liping
Author_Institution :
Key Lab. of Process Optimization & Intell. Decision-Making, Hefei Univ. of Technol., Hefei, China
fYear :
2010
fDate :
13-15 Aug. 2010
Firstpage :
67
Lastpage :
71
Abstract :
This paper introduces Copula approach, which has been widely used in statistical field, to the construction of OLAP cubes for the first time. Based on this approach, a novel scheme is proposed to compress data and answer any OLAP query without accessing raw data. The procedure of this scheme can be generally divided into three steps. Firstly, find the proper distribution functions to fit the marginal distribution of each attribute. Secondly, employ Copula approach to catch the intra relationship among attributes in a data set. Finally, use the probability density function of joint distribution to calculate the aggregation function. Empirical evidence shows that this Copula-based model can not only drastically reduce storage requirements but also save the query response time, while the accuracy is bounded under a given level.
Keywords :
data compression; data handling; data mining; probability; query processing; OLAP cube compression; aggregation function; copula based model; data compression; distribution function; online analytical processing; probability density function; query response time; raw data; statistical field; Aggregates; Computational modeling; Data models; Distribution functions; Equations; Joints; Mathematical model; Copula; Data cube compression; Distribution function; OLAP;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Business Intelligence and Financial Engineering (BIFE), 2010 Third International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-7575-9
Type :
conf
DOI :
10.1109/BIFE.2010.26
Filename :
5621731
Link To Document :
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