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ICCBR
2007
Springer

A Methodology for Analyzing Case Retrieval from a Clustered Case Memory

14 years 5 months ago
A Methodology for Analyzing Case Retrieval from a Clustered Case Memory
Abstract. Case retrieval from a clustered case memory consists in finding out the clusters most similar to the new input case, and then retrieving the cases from them. Although the computational time is improved, the accuracy rate may be degraded if the clusters are not representative enough due to data geometry. This paper proposes a methodology for allowing the expert to analyze the case retrieval strategies from a clustered case memory according to the required computational time improvement and the maximum accuracy reduction accepted. The mechanisms used to assess the data geometry are the complexity measures. This methodology is successfully tested on a case memory organized by a Self-Organization Map.
Albert Fornells, Elisabet Golobardes, Josep Maria
Added 08 Jun 2010
Updated 08 Jun 2010
Type Conference
Year 2007
Where ICCBR
Authors Albert Fornells, Elisabet Golobardes, Josep Maria Martorell, Josep Maria Garrell i Guiu, Núria Macià, Ester Bernadó i Mansilla
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