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

  • Juan A. Recio-García
  • Derek Bridge
  • Belén Díaz-Agudo
  • Pedro A. González-Calero
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5239)


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.


Case Base Recommender System Semantic Feature Software Reuse Reusable Component 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Juan A. Recio-García
    • 1
  • Derek Bridge
    • 2
  • Belén Díaz-Agudo
    • 1
  • Pedro A. González-Calero
    • 1
  1. 1.Department of Software Engineering and Artificial IntelligenceUniversidad Complutense de MadridSpain
  2. 2.Department of of Computer ScienceUniversity College CorkIreland

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