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Knowledge Base Systems

Definition. Knowledge Based Systems (KBS) are Artificial Intelligence based tools that work on knowledge base for effective decision making in more human oriented way using the expert knowledge stored in it.

Software that uses artificial intelligence or expert system techniques in problem solving process. It incorporates a store (database) of expert knowledge with couplings and linkages designed to facilitate its retrieval in response to specific queries, or to transfer expertise from one domain of knowledge to another.

KBS Advantages and Limitations

Knowledge-base systems are more useful in many situations than the traditional computer based information systems. Some major situations include:

•    When expert is not available.
•    When expertise is to be stored for future use or when expertise is to be cloned or multiplied.
•    When intelligent assistance and/or training are required for the decision making for problems solving.
•    When more than one experts’ knowledge have to be grouped at one platform.

With the proper utilization of knowledge the knowledge-based systems increase productivity, document rare knowledge by capturing scare expertise, and enhance problems solving capabilities in most flexible way. Such systems also document knowledge for future use and training. This leads to increased quality in problems solving process. However, the scarcity and nature of knowledge make the KBS development process difficult and complex. The transparent and abstract nature of knowledge is mainly responsible for this. In addition, this field needs more guidelines to accelerate the development process. Following are some of the major limitations with the KBS:

(i)    Acquisition, representation and manipulation of the large volume of the data/information/knowledge.

(ii)    High-tech image of the AI field.

(iii)    Abstract nature of the knowledge.

(iv)    Limitations of cognitive science and other scientific methods.

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