A Particle Swarm Optimization Approach for the Case Retrieval Stage in CBR

  • Nabila Nouaouria
  • Mounir Boukadoum
Conference paper


Finding the good experiment to reuse from the case memory is the key of success in Case Based Reasoning (CBR). The paper presents a novel associative memory model to perform this task. The algorithm is founded on a Particle Swarm Optimization (PSO) approach to compute the neighborhood of a new problem. Then, direct access to the cases in the neighborhood is performed. The model was experimented on the Adult dataset, acquired from the University of California at Irvine Machine Learning Repository and compared to flat memory model for performance. The obtained results are very promising.


Particle Swarm Optimization Particle Swarm Optimization Algorithm Memory Model Case Base Reasoning Memory Organization 
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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of Quebec at MontrealMontréalCanada

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