Abstract
Publisher Summary This chapter presents a methodology and tool for knowledge acquisition in the second version of the KEATS (The Knowledge Engineer's Assistant) system. This account emphasized the progression from knowledge elicitation through data analysis and domain conceptualization. The development of KEATS was motivated by the idea of building a knowledge engineering toolkit that could provide a comprehensive range of tools to help the knowledge engineer fill the gap between the raw data and final system. The KEATS-2 project as a whole aims to address some of the frontline problems of knowledge engineering. These include: (1) very large knowledge bases, it discusses how enormous knowledge bases could be implemented and maintained by a team of engineers in a clear and consistent manner, using knowledge derived from disparate sources. (2) Learning—current research indicates that the acquisition of expertise by humans is an intensive process requiring the refinement of both declarative and procedural knowledge over a period of years. (3) Common sense reasoning, and (4) environments. Tackling these problems will require a fruitful combination of empirical research, top–down methodologies and supporting environments. Work on Acquist and KEATS-2 as a whole continues in this spirit, and future results are eagerly awaited.
Published Version
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