Publication Type
Conference Proceeding Article
Version
submittedVersion
Publication Date
4-2011
Abstract
We propose a framework for efficient OLAP on information networks with a focus on the most interesting kind, the topological OLAP (called “T-OLAP”), which incurs topological changes in the underlying networks. T-OLAP operations generate new networks from the original ones by rolling up a subset of nodes chosen by certain constraint criteria. The key challenge is to efficiently compute measures for the newly generated networks and handle user queries with varied constraints. Two effective computational techniques, T-Distributiveness and T-Monotonicity are proposed to achieve efficient query processing and cube materialization. We also provide a T-OLAP query processing framework into which these techniques are weaved. To the best of our knowledge, this is the first work to give a framework study for topological OLAP on information networks. Experimental results demonstrate both the effectiveness and efficiency of our proposed framework.
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Publication
Database Systems for Advanced Applications: 16th International Conference, DASFAA 2011, Hong Kong, China, April 22-25, 2011, Proceedings, Part I
Volume
6587
First Page
389
Last Page
403
ISBN
9783642201486
Identifier
10.1007/978-3-642-20149-3_29
Publisher
Springer Verlag
City or Country
Berlin
Citation
QU, Qiang; ZHU, Feida; YAN, Xifeng; HAN, Jiawei; YU, Philip; and LI, Hongyan.
Efficient Topological OLAP on Information Networks. (2011). Database Systems for Advanced Applications: 16th International Conference, DASFAA 2011, Hong Kong, China, April 22-25, 2011, Proceedings, Part I. 6587, 389-403.
Available at: https://ink.library.smu.edu.sg/sis_research/1352
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://dx.doi.org/10.1007/978-3-642-20149-3_29
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons