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Integration of a Methodology for Cluster-Based Retrieval in jColibri

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Case-Based Reasoning Research and Development (ICCBR 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5650))

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Abstract

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. Although many authors have focused on proposing case memory organizations for improving the retrieval performance, there is not any free open source framework which offers this kind of capabilities. This work presents a plug-in called Thunder for the jcolibri framework. Thunder provides a methodology integrated in a graphical environment for managing the case retrieval from cluster based organizations. A case study based on tackling a Textual CBR problem using Self-Organizing Maps as case memory organizing technique is successfully tested.

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Fornells, A., Recio-García, J.A., Díaz-Agudo, B., Golobardes, E., Fornells, E. (2009). Integration of a Methodology for Cluster-Based Retrieval in jColibri. In: McGinty, L., Wilson, D.C. (eds) Case-Based Reasoning Research and Development. ICCBR 2009. Lecture Notes in Computer Science(), vol 5650. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02998-1_30

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  • DOI: https://doi.org/10.1007/978-3-642-02998-1_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02997-4

  • Online ISBN: 978-3-642-02998-1

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