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Evaluating CBR Systems Using Different Data Sources: A Case Study
 

Summary: Evaluating CBR Systems Using Different Data
Sources: A Case Study
Mingyang Gu and Agnar Aamodt
Department of Computer and Information Science, Norwegian University of Science
and Technology, Sem Saelands vei 7-9, N-7491, Trondheim, Norway
{mingyang,agnar}@idi.ntnu.no
Abstract. The complexity and high construction cost of case bases
make it very difficult, if not impossible, to evaluate a CBR system, es-
pecially a knowledge-intensive CBR system, using statistical evaluation
methods on many case bases. In this paper, we propose an evaluation
strategy, which uses both many simple case bases and a few complex
case bases to evaluate a CBR system, and show how this strategy may
satisfy different evaluation goals. The identified evaluation goals are clas-
sified into two categories: domain-independent and domain-dependent.
For the evaluation goals in the first category, we apply the statistical
evaluation method using many simple case bases (for example, UCI data
sets); for evaluation goals in the second category, we apply different,
relatively weak, evaluation methods on a few complex domain-specific
case bases. We apply this combined evaluation strategy to evaluate our
knowledge-intensive conversational CBR method as a case study.

  

Source: Aamodt, Agnar - Department of Computer and Information Science, Norwegian University of Science and Technology

 

Collections: Computer Technologies and Information Sciences