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Ranking Algorithms for Costly Similarity Measures

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Book cover Case-Based Reasoning Research and Development (ICCBR 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2080))

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Abstract

Case retrieval for e-commerce product recommendation is an application of CBR that demands particular attention to efficient implementation. Users expect quick response times from on-line catalogs, regardless of the underlying technology. In FindMe systems research, the cost of metric application has been a primary impediment to efficient retrieval. This paper describes several types of general and special-purpose ranking algorithms for case retrieval and evaluates their impact on retrieval efficiency with the Entree restaurant recommender.

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References

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Author information

Authors and Affiliations

  1. Dept. of Information Systems and Decision Sciences, California State University, Fullerton, USA

    Robin Burke

Authors
  1. Robin Burke
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Editor information

Editors and Affiliations

  1. Naval Research Laboratory, Code 5510, Navy Center for Applied Research in Artificial Intelligence, 4555 OverlookAvenue, SW, Washington, DC, 20375, USA

    David W. Aha

  2. Computer Science Department, University of Auckland, Private Bag 92019, Auckland 1, New Zealand

    Ian Watson

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© 2001 Springer-Verlag Berlin Heidelberg

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Burke, R. (2001). Ranking Algorithms for Costly Similarity Measures. In: Aha, D.W., Watson, I. (eds) Case-Based Reasoning Research and Development. ICCBR 2001. Lecture Notes in Computer Science(), vol 2080. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44593-5_8

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  • DOI: https://doi.org/10.1007/3-540-44593-5_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42358-4

  • Online ISBN: 978-3-540-44593-7

  • eBook Packages: Springer Book Archive

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