Visualizing and Evaluating Complexity of Textual Case Bases

  • Sutanu Chakraborti
  • Ulises Cerviño Beresi
  • Nirmalie Wiratunga
  • Stewart Massie
  • Robert Lothian
  • Deepak Khemani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5239)


This paper deals with two relatively less well studied problems in Textual CBR, namely visualizing and evaluating complexity of textual case bases. The first is useful in case base maintenance, the second in making informed choices regarding case base representation and tuning of parameters for the TCBR system, and also for explaining the behaviour of different retrieval/classification techniques over diverse case bases. We present an approach to visualize textual case bases by “stacking” similar cases and features close to each other in an image derived from the case-feature matrix. We propose a complexity measure called GAME that exploits regularities in stacked images to evaluate the alignment between problem and solution components of cases. GAME class , a counterpart of GAME in classification domains, shows a strong correspondence with accuracies reported by standard classifiers over classification tasks of varying complexity.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Sutanu Chakraborti
    • 1
  • Ulises Cerviño Beresi
    • 2
  • Nirmalie Wiratunga
    • 2
  • Stewart Massie
    • 2
  • Robert Lothian
    • 2
  • Deepak Khemani
    • 3
  1. 1.Systems Research LabTata Research Development and Design CentrePuneIndia
  2. 2.School of ComputingThe Robert Gordon UniversityScotlandUK
  3. 3.Department of Computer Science and EngineeringIndian Institute of Technology, MadrasChennaiIndia

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