A quantitative analysis of the robustness of knowledge-based systems through degradation studies

The overall aim of this paper is to provide a general setting for quantitative quality measures of knowledge-based system behaviour that is widely applicable to many knowledge-based systems. We propose a general approach that we call degradation studies: an analysis of how system output changes as a...

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Bibliographic Details
Published in:Knowledge and information systems 2005-02, Vol.7 (2), p.224-245
Main Authors: Groot, Perry, ten Teije, Annette, van Harmelen, Frank
Format: Article
Language:English
Subjects:
Case studies
Degradation
Expert systems
Feasibility studies
Information systems
Input output analysis
Knowledge
Knowledge base
Quantitative analysis
Robustness
Software
Studies
Systems analysis
Taxonomy
Vegetation
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Summary:The overall aim of this paper is to provide a general setting for quantitative quality measures of knowledge-based system behaviour that is widely applicable to many knowledge-based systems. We propose a general approach that we call degradation studies: an analysis of how system output changes as a function of degrading system input, such as incomplete or incorrect data or knowledge. To show the feasibility of our approach, we have applied it in a case study. We have taken a large and realistic vegetation-classification system, and have analysed its behaviour under various varieties of incomplete and incorrect input. This case study shows that degradation studies can reveal interesting and surprising properties of the system under study. [PUBLICATION ABSTRACT]
ISSN:0219-1377
0219-3116
DOI:10.1007/s10115-003-0140-7