Integration of a Methodology for Cluster-Based Retrieval in jColibri

  • Authors:
  • Albert Fornells;Juan Antonio Recio-García;Belén Díaz-Agudo;Elisabet Golobardes;Eduard Fornells

  • Affiliations:
  • Grup de Recerca en Sistemes Intel·ligents, La Salle - Universitat Ramon Llull, Barcelona, Spain 08022;Department of Software Engineering and Artificial Intelligence, Universidad Complutense de Madrid, Spain;Department of Software Engineering and Artificial Intelligence, Universidad Complutense de Madrid, Spain;Grup de Recerca en Sistemes Intel·ligents, La Salle - Universitat Ramon Llull, Barcelona, Spain 08022;Grup de Recerca en Sistemes Intel·ligents, La Salle - Universitat Ramon Llull, Barcelona, Spain 08022

  • Venue:
  • ICCBR '09 Proceedings of the 8th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
  • Year:
  • 2009

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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.