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Deriving knowledge representation guidelines by analyzing knowledge engineer behavior
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DOI：10.1016/j.dss.2012.05.038.png)
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Abstract
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Knowledge engineering research has focused on proposing knowledge acquisition techniques, developing and evaluating knowledge representation schemes and engineering tools, and testing and debugging knowledge-based systems. Few formal studies have been conducted on understanding the behaviors and roles of knowledge engineers. Applying the theory of mental models, this paper describes a think aloud verbal protocol study to determine an empirical basis for understanding: (1) how knowledge engineers extract domain knowledge from textual sources; and (2) the cognitive mechanisms by which they engage various knowledge representation schemes to represent that knowledge acquired. The results suggest that knowledge representation is not simply a translation of acquired knowledge to a knowledge representation. Instead, it is an iterative process of selective querying of acquired knowledge, and continuous refinement of a model leveraging, not only on acquired knowledge from domain experts, but also from the knowledge engineer. From the findings of empirical studies, a set of guidelines is derived to support the training and development of better knowledge representation schemes, representation processes, and knowledge engineering tools. (C) 2012 Elsevier B.V. All rights reserved.
Keywords:
Knowledge engineering
Knowledge representation
Problem behavior graph
Protocol analysis
Theory of mental models
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