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Book Contents

Ch. 10
Building Knowledge-Driven DSS and Mining Data

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Advantages and Limitations of Rules

Using an inference engine with rules is the most common development environment for Knowledge-Driven DSS. Rules are easy to understand. Also, explanations are easy to provide when you store knowledge as rules. From a developerís perspective, modification and maintenance of the knowledge base is relatively easy. A developer can also easily combine uncertainty knowledge with rules. There are, however, a number of major limitations of using this development approach. First, and most important, complex knowledge is difficult to represent using rules. Also, when rules are used the knowledge represented tends to be superficial. Knowledge-Driven DSS builders usually like developing systems based on rules, but using rules will not work for all applications.

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