Subspace discovery for promotion: A cell clustering approach

Tianyi Wu, Jiawei Han

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


The promotion analysis problem has been proposed in 16, where ranking-based promotion query processing techniques are studied to effectively and efficiently promote a given object, such as a product, by exploring ranked answers. To be more specific, in a multidimensional data set, our goal is to discover interesting subspaces in which the object is ranked high. In this paper, we extend the previously proposed promotion cube techniques and develop a cell clustering approach that is able to further achieve better tradeoff between offline materialization and online query processing. We formally formulate our problem and present a solution to it. Our empirical evaluation on both synthetic and real data sets show that the proposed technique can greatly speedup query processing with respect to baseline implementations.

Original languageEnglish (US)
Title of host publicationDiscovery Science - 12th International Conference, DS 2009, Proceedings
Number of pages15
StatePublished - 2009
Event12th International Conference on Discovery Science, DS 2009 - Porto, Portugal
Duration: Oct 3 2009Oct 5 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5808 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other12th International Conference on Discovery Science, DS 2009

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Subspace discovery for promotion: A cell clustering approach'. Together they form a unique fingerprint.

Cite this