Probabilistic similarity networks
著者
書誌事項
Probabilistic similarity networks
（ACM doctoral dissertation awards, 1990）
MIT Press, c1991
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注記
Bibliography: p. [223]-230
Includes index
内容説明・目次
内容説明
In this blend of formal theory and practical application, David Heckerman develops methods for building normative expert systems - expert systems that encode knowledge in a decision-theoretic framework. Heckerman introduces the similarity network and partition, two extensions to the influence diagram representation. He uses the new representations to construct Pathfinder, a large, normative expert system for the diagnosis of lymph-node diseases. Heckerman shows that such expert systems can be built efficiently, and that the use of a normative theory as the framework for representing knowledge can dramatically improve the quality of expertise that is delivered to the user. He concludes with a formal evaluation of the power of his methods for building normative expert systems.
目次
- Similarity networks and partitions - a simple example
- theory of similarity networks
- Pathfinder - a case study
- an evaluation of Pathfinder
- conclusions and future work.
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