Knowledge Representation
The term knowledge representation is the area of computer science where scientists try to model human behaviour. It is closely linked with Artificial Intelligence (AI). The concept is to understand a subject area including all the facts and concepts, as well as the relations among them and the mechanisms for how to combine them to solve problems within that area.
“Since no organism can cope with infinite diversity, one of the basic functions of all organisms is the cutting up of the environment into classifications by which non-identical stimuli can be treated as equivalent….”
(Rosch, 1978 cited in Luger, 2002 pp.197)
The goal of AI is to design computer programs. Which can do things that human call ‘intelligent’. Although the study of AI is relatively new, the foundations of it is logic and can be traced back to ancient Greece. Aristotle is considered to be the father of logic. The Semantic Web depends on the ability to associate formal meaning with content. The field of knowledge representation provides a good starting point for the design of a Semantic Web language. It offers insight into the design and use of languages that attempt to formalise meaning. Knowledge representation is vital in the development of the Semantic Web. Computers will need access to structured collections of information and inference rules that they can use to conduct automated reasoning.
Research in the field has spawned a number of knowledge representation languages. Each with its own set of features. These will be written about in later posts.
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