Efficient topological OLAP on information networks

Qiang Qu, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu, Hongyan Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.

Original languageEnglish (US)
Title of host publicationDatabase Systems for Advanced Applications - 16th International Conference, DASFAA 2011, Proceedings
Number of pages15
EditionPART 1
StatePublished - 2011
Externally publishedYes
Event16th International Conference on Database Systems for Advanced Applications, DASFAA 2011 - Hong Kong, China
Duration: Apr 22 2011Apr 25 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6587 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other16th International Conference on Database Systems for Advanced Applications, DASFAA 2011
CityHong Kong

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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