Deriving knowledge representation guidelines by analyzing knowledge engineer behavior

  • Authors:

  • Cecil Eng Huang Chua;Veda C. Storey;Roger H. L. Chiang

  • Affiliations:

  • Information Systems and Operations Management Department, University of Auckland Business School, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand;J. Mack Robinson College of Business, Georgia State University, Atlanta GA 30302-4015, USA;Department of Operations, Business Analytics, and Information Systems, Carl H. Lindner College of Business, University of Cincinnati, Cincinnati, OH 45221, USA

  • Venue:
  • Decision Support Systems
  • Year:
  • 2012

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Abstract

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.