Retrieval Based on Self-explicative Memories

  • Albert Fornells
  • Eva Armengol
  • Elisabet Golobardes
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5239)


One of the key issues in Case-Based Reasoning (CBR) systems is the efficient retrieval of cases when the case base is huge and/or it contains uncertainty and partial knowledge. We tackle these issues by organizing the case memory using an unsupervised clustering technique to identify data patterns for promoting all CBR steps. Moreover, another useful property of these patterns is that they provide to the user additional information about why the cases have been selected and retrieved through symbolic descriptions. This work analyses the introduction of this knowledge in the retrieve phase. The new strategies improve the case retrieval configuration procedure.


Case Retrieval Case Memory Organization Self-Explicative Memories Soft Case-Based Reasoning Self-Organizing Map 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Albert Fornells
    • 1
  • Eva Armengol
    • 2
  • Elisabet Golobardes
    • 1
  1. 1.Grup de Recerca en Sistemes Intel·ligents Enginyeria i Arquitectura La SalleUniversitat Ramon LlullBarcelona(Spain)
  2. 2.IIIA - Artificial Intelligence Research InstituteCSIC - Spanish Council for Scientific ResearchBellaterra(Spain)

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