Knowledge representation

Knowledge representation is needed for library classification and for processing concepts in an information system. In the field of artificial intelligence, problem solving can be simplified by an appropriate choice of knowledge representation. Representing the knowledge in one way may make the solution simple, while an unfortunate choice of representation may make the solution difficult or obscure; the analogy is to make computations in Arabic numerals or in Roman numerals; long division is simpler in one and harder in the other. Likewise, there is no representation that can serve all purposes or make every problem equally approachable.


Links and structures

While hyperlinks have come into widespread use, the closely related semantic link is not yet widely used. The mathematical table has been used since Babylonian times. More recently, these tables have been used to represent the outcomes logic operations, as truth tables, which were used to study and model Boolean logic, for example. Spreadsheets are yet another tabular representation of knowledge. Other knowledge representations are trees, by means of which the connections among fundamental concepts and derivitive concepts can be shown.

Storage and manipulation

One problem in knowledge representation consists of how to store and manipulate knowledge in an information system in a formal way so that it may be used by mechanisms to accomplish a given task. Examples of applications are expert systems, machine translation systems, computer-aided maintenance systems and information retrieval systems (including database front-ends).

Language and notation

Some people think it would be best to represent knowledge in the same way that it is represented in human mind, which is the only known working intelligence so far, or to represent knowledge in the form of human language. Unfortunately, we don't know how knowledge is represented in the human mind, or how to manipulate human languages the same way that the human mind does it. One clue is that primates know how to use point and click user interfaces; thus the gesture-based interface appears to be part of our cognitive apparatus, a modality which is not tied to verbal language, and which exists in other animals besides humans.

For this reason, various artificial languages and notations have been proposed for representing knowledge. They are typically based on logic and mathematics, and have easily parsed grammars to ease machine processing.


The recent fashion in knowledge representation languages is to use XML as the low-level syntax. This tends to make the output of these KR languages easy for machines to parse, at the expense of human readability.

First-order predicate calculus is commonly used as a mathematical basis for these systems, to avoid excessive complexity. However, even simple systems based on this simple logic can be used to represent data that is well beyond the processing capability of current computer systems: see computability for reasons.

Examples of notations:


Examples of artificial languages intended for knowledge representation include:

  • CycL
  • Loom
  • OWL
  • KM : the Knowledge Machine (frame-based language used for knowledge representation work)

Techniques of knowledge representation

Semantic networks may be used to represent knowledge. Each node represents a concept and arcs are used to define relations between the concepts.

From the 1960s, the knowledge frame or just frame has been used. A frame consists of slots which contain values; for instance, the frame for house might contain a color slot, number of floors slot, etc.

Frames can behave something like object-oriented programming languages, with inheritance of features described by the "is-a" link. However, there has been no small amount of inconsistency in the usage of the "is-a" link: Ronald J. Brachman wrote a paper titled "What IS-A is and isn't", wherein 29 different semantics were found in projects whose knowledge representation schemes involved an "is-a" link. Other links include the "has-part" link.

Frame structures are well-suited for the representation of schematic knowledge and stereotypical cognitive patterns. The elements of such schematic patterns are weighted unequally, attributing higher weights to the more typical elements of a schema ( A pattern is activated by certain expectations: If a person sees a big bird, he or she will classify it rather as a sea eagle than a golden eagle, assuming that his or her "sea-scheme" is currently activated and his "land-scheme" is not.

Frames representations are more object-centers than semantic networks: All the facts and properties of a concept are located in one place - there is no need for costly search processes in the database.

Frames suffer from the frame problem of knowledge linking.

A script is a type of frame that describes what happens temporally; the usual example given is that of describing going to a restaurant. The steps include waiting to be seated, receiving a menu, ordering, etc.

See also


  • Ronald J. Brachman; What IS-A is and isn't. An Analysis of Taxonomic Links in Semantic Networks; IEEE Computer, 16 (10); October 1983 [1] (
  • Jean-Luc Hainaut, Jean-Marc Hick, Vincent Englebert, Jean Henrard, Didier Roland: Understanding Implementations of IS-A Relations. ER 1996: 42-57 [2] (

External links

de:Wissensreprsentation fr:Reprsentation des connaissances zh:知识表现 th:การแทนความรู้ uk:Представлення знань


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