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Rule-Based Training of Neural Networks

Faisal, Kanaan A (1991) Rule-Based Training of Neural Networks. Journal of Expert Systems with applications, 2 (1). pp. 47-58.

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Rule-based expert systems either develop out of the direct involvement of a concerned expert or through the enormous efforts of intermediaries called knowledge engineers . In either case, knowledge engineering tools are inadequate in many ways to support the complex problem of expert system building. This article describes a set of experiments with adaptive neural networks which explore two types of learning, deductive and inductive, in the context of a rule-based, deterministic parser of Natural Language. Rule-based processing of Language is an important and complex domain. Experiences gained in this domain generalize to other rule-based domains. We report on those experiences and draw some general conclusions that are relevant to knowledge engineering activities and maintenance of rule-based systems.

Item Type:Article
Date Type:Publication
Divisions:College Of Computer Sciences and Engineering > Information and Computer Science Dept
Creators:Faisal, Kanaan A
ID Code:10654
Deposited On:25 Jun 2008 15:00
Last Modified:12 Apr 2011 13:15

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