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Automating the Discovery of Recommendation Rules

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Research and Development in Intelligent Systems XXI (SGAI 2004)

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Abstract

We present techniques for the discovery of recommendation rules that describe the behaviour of a recommender system in localised areas of the product space. Potential uses of the discovered rules include assessing the performance of the system in terms of recommendation efficiency and solution quality. For example, the discovered rules may reveal potential efficiency gains that might be achieved with an alternative recommendation strategy. We also present an efficient algorithm for automating the discovery of recommendation rules in nearest-neighbour (NN) retrieval, the standard approach to product recommendation in case-based reasoning (CBR).

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Author information

Authors and Affiliations

  1. School of Computing and Information Engineering, University of Ulster, Coleraine, BT52 1SA, Northern Ireland

    David McSherry

Authors
  1. David McSherry
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Editor information

Editors and Affiliations

  1. Faculty of Technology, University of Portsmouth, Portsmouth, UK

    Max Bramer BSc, PhD, CEng, FBCS, FIEE, FRSA

  2. Department of Computer Science, University of Liverpool, Liverpool, UK

    Frans Coenen

  3. Nottingham Trent University, UK

    Tony Allen

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© 2005 Springer-Verlag London Limited

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McSherry, D. (2005). Automating the Discovery of Recommendation Rules. In: Bramer, M., Coenen, F., Allen, T. (eds) Research and Development in Intelligent Systems XXI. SGAI 2004. Springer, London. https://doi.org/10.1007/1-84628-102-4_7

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  • DOI: https://doi.org/10.1007/1-84628-102-4_7

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-85233-907-4

  • Online ISBN: 978-1-84628-102-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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