To address the problems of representing complex information, the CKR-1 representation scheme is implemented. Deep knowledge about a complex object, event, circumstance, or process is known as complex knowledge. Samples of technical expertise from the insurance sector are used to describe the essence of complex knowledge. These examples demonstrate the scheme’s effectiveness as well as its shortcomings. Simple and abstract concepts, events, actions, and situations are supported by CKR-1, a form of semantic network. It also supports a variety of relationship styles, such as corporation, logical, causal, and process relationships. Its expressivity stems from its ability to accommodate abstractions, elaborations, assertions, and multiple points of view. A randomised collection of fifty information items from a book for insurance professionals were used to assess usability. The system treated 39 of them admirably. Despite this, the scheme has drawbacks due to the complexity of explaining concepts that include many other vaguely described abstract concepts.
Author (s) Details
Chandra S. Amaravadi
School of Computer Sciences, Western Illinois University, USA.
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