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Multidimensional Recommender Systems: A Data Warehousing Approach

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Electronic Commerce (WELCOM 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2232))

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Abstract

In this paper, we present a new data-warehousing-based approach to recommender systems. In particular, we propose to extend traditional two-dimensional user/item recommender systems to support multiple dimensions, as well as comprehensive profiling and hierarchical aggregation (OLAP) capabilities. We also introduce a new recommendation query language RQL that can express complex recommendations taking into account the proposed extensions. We describe how these extensions are integrated into a framework that facilitates more flexible and comprehensive user interactions with recommender systems.

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Author information

Authors and Affiliations

  1. Computer Science Department, New York University, Courant Institute of Mathematical Sciences, 10012, New York, NY, USA

    Gediminas Adomavicius

  2. Information Systems Department, New York University, Stern School of Business, 10012, New York, NY, USA

    Alexander Tuzhilin

Authors
  1. Gediminas Adomavicius
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  2. Alexander Tuzhilin
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Editor information

Editors and Affiliations

  1. Darmstadt University of Technology, Wilhelminenstr.7, 64283, Darmstadt, Germany

    Ludger Fiege  & Gero Mühl  & 

  2. T-Nova, Otto-Röhm-Str.71C, 64293, Darmstadt, Germany

    Uwe Wilhelm

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© 2001 Springer-Verlag Berlin Heidelberg

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Adomavicius, G., Tuzhilin, A. (2001). Multidimensional Recommender Systems: A Data Warehousing Approach. In: Fiege, L., Mühl, G., Wilhelm, U. (eds) Electronic Commerce. WELCOM 2001. Lecture Notes in Computer Science, vol 2232. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45598-1_17

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  • DOI: https://doi.org/10.1007/3-540-45598-1_17

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42878-7

  • Online ISBN: 978-3-540-45598-1

  • eBook Packages: Springer Book Archive

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