Fuzzy attributes for knowledge representation and acquisition

Robert L. Kelsey; Robert B. Webster

doi:10.1117/12.243267

14 June 1996 Fuzzy attributes for knowledge representation and acquisition

Robert L. Kelsey, Robert B. Webster

Proceedings Volume 2761, Applications of Fuzzy Logic Technology III; (1996) https://doi.org/10.1117/12.243267
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

Abstract

Repertory grids and other matrix-like structures can be used to represent knowledge and elicit knowledge from experts. A grid or matrix is a representation of a knowledge domain where the elements in the domain appear along the horizontal axis and constructs or attributes of the elements appear along the vertical axis. Each construct is rated for its presence in a given element or how much a construct applies to an element. Analysis of these ratings can determine similarities and differences between the elements. Traditionally, constructs are bipolar entities where a rating falls on a range from one pole to the other. For example, temperature may be represented by the bipolar construct hot-cold and a range of 1 to 5 in which 1 represents hot and 5 represents cold. Ratings of 2, 3, and 4 lie in-between hot and cold. Additionally, all constructs in a grid have the same range of values and the range is arbitrarily chosen. This paper presents a method for translating grid ratings into fuzzy membership values. The fuzzy membership values become the values for describing and analyzing the associations between elements. Thus, constructs no longer need to use the same scaling range and no longer need to be bipolar. A construct of an element now becomes a true attribute of an element. An attribute can be rated in its own range and with its own unit of measurement. In the previous example, the bipolar construct hot-cold becomes simply, temperature measured in degrees. Experts or users need no longer translate to an artificial rating range.

Citation Download Citation

Robert L. Kelsey and Robert B. Webster "Fuzzy attributes for knowledge representation and acquisition", Proc. SPIE 2761, Applications of Fuzzy Logic Technology III, (14 June 1996); https://doi.org/10.1117/12.243267

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KEYWORDS

Fuzzy logic

Control systems

Composites

Databases

Temperature metrology

Human-computer interaction

Information technology

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