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Subspace Discovery for Promotion: A Cell Clustering Approach

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Discovery Science (DS 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5808))

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Abstract

The promotion analysis problem has been proposed in , 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.

The work was supported in part by the U.S. National Science Foundation grants IIS-08-42769 and BDI- 05-15813, and the Air Force Office of Scientific Research MURI award FA9550-08-1-0265.

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Author information

Authors and Affiliations

  1. University of Illinois at Urbana-Champaign, USA

    Tianyi Wu & Jiawei Han

Authors
  1. Tianyi Wu
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  2. Jiawei Han
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Editor information

Editors and Affiliations

  1. Faculty of Economics; Rua Dr. Roberto Frias, University of Porto, 4200-465, Porto, Portugal

    João Gama

  2. DCC-FC, Universidade do Porto, Portugal

    Vítor Santos Costa

  3. LIACC/FEP, Universidade do Porto, Portugal

    Alípio Mário Jorge

  4. LIAAD-INESC Porto L.A./Faculty of Economics, University of Porto, Rua de Ceuta, 118-6, 4050-190, Porto, Portugal

    Pavel B. Brazdil

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© 2009 Springer-Verlag Berlin Heidelberg

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Wu, T., Han, J. (2009). Subspace Discovery for Promotion: A Cell Clustering Approach. In: Gama, J., Costa, V.S., Jorge, A.M., Brazdil, P.B. (eds) Discovery Science. DS 2009. Lecture Notes in Computer Science(), vol 5808. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04747-3_28

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  • DOI: https://doi.org/10.1007/978-3-642-04747-3_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04746-6

  • Online ISBN: 978-3-642-04747-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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