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2010

Exploring Correlated Subspaces for Efficient Query Processing in Sparse Databases

10 years 8 months ago
Exploring Correlated Subspaces for Efficient Query Processing in Sparse Databases
The sparse data is becoming increasingly common and available in many real-life applications. However, relative little attention has been paid to effectively model the sparse data and existing approaches such as the conventional "horizontal" and "vertical" representations fail to provide satisfactory performance for both storage and query processing, as such approaches are too rigid and generally do not consider the dimension correlations. In this paper, we propose a new approach, named HoVer, to store and conduct query for sparse datasets in an unmodified RDBMS, where HoVer stands for Horizontal representation over Vertically partitioned subspaces. According to the dimension correlations of sparse datasets, a novel mechanism has been developed to vertically partition a high-dimensional sparse dataset into multiple lower dimensional subspaces, and all the dimensions are highly correlated intrasubspace and highly unrelated inter-subspace respectively. Therefore, orig...
Bin Cui, Jiakui Zhao, Dongqing Yang
Added 22 May 2011
Updated 22 May 2011
Type Journal
Year 2010
Where TKDE
Authors Bin Cui, Jiakui Zhao, Dongqing Yang
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