Efficient Topological OLAP on Information Networks

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 n...

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Bibliographic Details
Main Authors: QU, Qiang, ZHU, Feida, YAN, Xifeng, HAN, Jiawei, YU, Philip, LI, Hongyan
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2011
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Online Access:https://ink.library.smu.edu.sg/sis_research/1352
https://ink.library.smu.edu.sg/context/sis_research/article/2351/viewcontent/ZhuFD_2011_EfficientTopOlap.pdf
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Institution: Singapore Management University
Language: English
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Summary: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.