Knowledge Management
From knowledge bases to decision models
Wellman, M. P. | Breese, J. S. | Goldman, R.
Knowledge Engineering Review, 7 (1), 35-53.
A survey of knowledge acquisition techniques and tools
Knowledge Acquisition, 1[#1]:3-37
Preliminary steps toward a taxonomy of problem-solving methods
In Marcus, S., (Ed.), Automating Knowledge Acquisition for Knowledge Based Systems, chapter 8, pages 120-146. Boston: Kluwer Academic Publishers
Induction of decision trees
The technology for building knowledge-based systems by inductive inference from examples hasbeen demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail. Results from recent studies show ways in which the methodology can be modified to deal with information that is noisy and/or incomplete. A reported shortcoming of the basic algorithm is discussed and two means of overcoming it are compared. The paper concludes with illustrations of current research directionsMachine Learning, 1, p. 81-106
Semi-autonomous acquisition of pattern-based knowledge
This paper has three themes: (1) The task of acquiring and organizing the knowledge on which to base an expert system is difficult.(2) Inductive inference systems can be used to extract this knowledge from data.(3) The knowledge so obtained is powerful enough to enable systems using it to compete handily with more conventional algorithm-based systems.These themes are explored in the context of attempts to construct high-performance programs relevant to the chess endgame king-rook versus king-knight.In Hayes, J. E., Michie, D., and Pao, Y.-H. (Eds.), Machine Intelligence 10. Ellis Horwood.
New research on expert systems
In Hayes, J. E., Michie, D., and Pao, Y.-H. (Eds.), Machine Intelligence 10. Ellis Horwood.
The HEARSAY-II speech understanding system: Integrating knowledge to resolve uncertainty
ACM Computing Survey 12:213-253