Visualizing and Evaluating Complexity of Textual Case Bases

Authors:
Sutanu Chakraborti;Ulises Cerviño Beresi;Nirmalie Wiratunga;Stewart Massie;Robert Lothian;Deepak Khemani
Affiliations:
Systems Research Lab, Tata Research Development and Design Centre, Pune, India;School of Computing, The Robert Gordon University, Scotland, UK;School of Computing, The Robert Gordon University, Scotland, UK;School of Computing, The Robert Gordon University, Scotland, UK;School of Computing, The Robert Gordon University, Scotland, UK;Department of Computer Science and Engineering, Indian Institute of Technology, Madras, Chennai, India 36
Venue:
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Year:
2008

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Abstract

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. GAMEclass, a counterpart of GAME in classification domains, shows a strong correspondence with accuracies reported by standard classifiers over classification tasks of varying complexity.