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CBR for CBR: A Case-Based Template Recommender System for Building Case-Based Systems

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Advances in Case-Based Reasoning (ECCBR 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5239))

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Abstract

Our goal is to support system developers in rapid prototyping of Case-Based Reasoning (CBR) systems through component reuse. In this paper, we propose the idea of templates that can be readily adapted when building a CBR system. We define a case base of templates for case-based recommender systems. We devise a novel case-based template recommender, based on recommender systems research, but using a new idea that we call Retrieval-by-Trying. Our experiments with the system show that similarity based on semantic features is more effective than similarity based on behavioural features, which is in turn more effective than similarity based on structural features.

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Klaus-Dieter Althoff Ralph Bergmann Mirjam Minor Alexandre Hanft

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Recio-García, J.A., Bridge, D., Díaz-Agudo, B., González-Calero, P.A. (2008). CBR for CBR: A Case-Based Template Recommender System for Building Case-Based Systems. In: Althoff, KD., Bergmann, R., Minor, M., Hanft, A. (eds) Advances in Case-Based Reasoning. ECCBR 2008. Lecture Notes in Computer Science(), vol 5239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85502-6_31

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  • DOI: https://doi.org/10.1007/978-3-540-85502-6_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85501-9

  • Online ISBN: 978-3-540-85502-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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