Knowledge Normalization
HELP....Seeking advice on programming backward and forward chaining.
Normalizing knowledge is the foundation for developing custom business neuronets (Knowledge Engineering Storyboard modeling) in business applications.
Please recommend the video of the successful installation of the paradigm.
The IDC Story: The First Successful AI Based Multi-Expert System In Arizona.
Examine a multi-expert system generator, Rose Navigator, and an Enterprise Resource Plan to help manage the need for human engineers against the dynamics of customer expectations and orders.
Pages: 39 through 45, also pages 1 and 5.
www.pcai.com/web/6a72/522.11.42/TOC.htm copy and paste to browser.
JUNE 2004 Publication: PCAI Magazine.
The Heuristic Life Cycle of a multi-Expert system.
Introduction, the purpose of this article is to introduce a new paradigm in the discipline of engineering human knowledge.
Abstract This article introduces a new paradigm to the discipline of engineering human knowledge, one that we divide into four tenets of knowledge representation:
1. The four prime domains of knowledge.
2. All human knowledge has, at its root, a language to communicate the knowledge.
3. A single language sentence contains the smallest unit of knowledge, and it is possible to normalize and codify this unit of knowledge into a multi-expert computer system (Language representation).
4. A knowledge based computer system can learn as well as teach.
This paradigm, as illustrated in this article, is the result of research and development and the resulting creation of a multi expert system generator. The methodology of the multi-expert system generator is a self-designing system — it constructs and designs attributes that are an integral part of the methodology, process and architecture used to generate the multi-expert system.
Magazine Article:
http://www.pcai.com/web/6t6y6t/6t6y6y.7.02/TOC.htm copy and paste to browser.
or http://publicliterature.org/en/wikipedia/k/kn/knowledge_normalization.html
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