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Improving Case Representation and Case Base Maintenance in Recommender Agents

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Advances in Case-Based Reasoning (ECCBR 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2416))

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Abstract

Recommendations by salespeople are always based on knowledge about the products and expertise about your tastes, preferences, interests and behavior in the shop. In an attempt to model the behavior of salespeople, AI research has been focussed on the so called recommender agents. Such agents draw on previous results from machine learning and other advances in AI technology to develop user models and to anticipate and predict user preferences. In this paper we introduce a new approach to recommendation, based on Case-Based Reasoning (CBR). CBR is a paradigm for learning and reasoning through experience, as salesmen do. We present a user model based on cases in which we try to capture both explicit interests (the user is asked for information) and implicit interests (captured from user interaction) of a user on a given item. Retrieval is based on a similarity function that is constantly tuned according to the user model. Moreover, in order to cope with the utility problem that current CBR system suffer from, our approach includes a forgetting mechanism (the drift attribute) that can be extended to other applications beyond e-commerce.

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Author information

Authors and Affiliations

  1. Institut d’Informàtica i Aplicacions, Universitat de Girona, Campus Montilivi, 17071, Girona, Spain

    Miquel Montaner, Beatriz López & Josep Lluís de la Rosa

Authors
  1. Miquel Montaner
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  2. Beatriz López
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  3. Josep Lluís de la Rosa
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Editor information

Editors and Affiliations

  1. School of Computing, The Robert Gordon University, St. Andrew Street, Aberdeen, AB25 1HG, Scotland, UK

    Susan Craw

  2. Computing Science Department, University of Aberdeen, Aberdeen, AB24 3UE, Scotland, UK

    Alun Preece

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© 2002 Springer-Verlag Berlin Heidelberg

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Montaner, M., López, B., de la Rosa, J.L. (2002). Improving Case Representation and Case Base Maintenance in Recommender Agents. In: Craw, S., Preece, A. (eds) Advances in Case-Based Reasoning. ECCBR 2002. Lecture Notes in Computer Science(), vol 2416. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46119-1_18

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  • DOI: https://doi.org/10.1007/3-540-46119-1_18

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44109-0

  • Online ISBN: 978-3-540-46119-7

  • eBook Packages: Springer Book Archive

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