EECB: a knowledge elicitation tool based on repertory grid and city block metric

Abstract

There are several knowledge acquisition tools that use repertory grids as a technique to elicitate knowledge. One of the steps involved in this technique is the debugging of the grid using procedures based on cluster analysis. Most of these tools employ a Euclidean metric for the clustering. However, some authors find evidence that people use the city block metric when rating similarities. In this paper, the tool ComPar ( Comparación de Pares), developed to acquire data in a knowledge engineering experiment, is described. This tool tries to determine what kind of metric is the most often used by people in similarity judgments. After the experiment, it was concluded that there is evidence that individuals use mainly a city block metric when trying to judge similarity between different things. Accordingly, a tool supporting the repertory grid technique called EECB ( emparrillado euclı́deo, “city block” in Spanish) was developed afterwards, allowing the possibility of distance calculations using city block metric.