Knowledge is an an abstract term that attempt to capture an individual’s understanding of a given subject. If we have knowledge that is sufficient to solve a problem, we have to search our goal in the light of that knowledge. Knowledge can be divided into following three type.
1. Procedural Knowledge
Procedural knowledge is compiled or processed form of information. Procedural knowledge is related to the performance of some task. for example, sequence of step to solve a particular problem is procedural knowledge.
2. Declarative Knowledge
Declarative knowledge is passive knowledge in the form of statement of facts about the world. for example, Delhi is the capital of India.
3. Heuristic Knowledge
Heuristic knowledge are rules of thumb or tricks. Heuristic knowledge is used to make judgments and also to simplify solutions of problems.
In solving the problem, we must represent knowledge. There are two entities to deal with:
- Facts: Truth about the real world. These are the things we want to represent. This can be represented as knowledge level.
- Representation of the Facts: Representation of fact in some chosen formalism. These are the thing with which we actually manipulate data. This can be regarded as the symbol level since we usually define the representation in terms of symbols that can be manipulated by programs.
Thus knowledge is a collection of facts from some domain. We need a representation of facts that can be manipulated by a program. Normal English is insufficient, to hard currently for a computer program to draw inference in natural languages. Thus some of symbolic representation is necessary. This intermediate mechanism requires some type of forward and backward mapping between facts and symbols.
Knowledge Representation Scheme
There are four schemes of knowledge representation.
1. Logical Scheme
Logical schemes represent knowledge, using mathematical symbols, inference rules and are based on precisely defined syntax and semantics. examples: predicate calculus, propositional calculus.
2. Procedural Scheme
In procedural schemes knowledge is represented as a set of instruction for problem solving. It allows to modify a knowledge base easily and separate knowledge base and inference mechanism. example: IF..THEN… rules.
3. Networked Scheme
Network schemes uses a graph to represent knowledge. Nodes of a graph display objects or concept in domain and arcs (edges) defines relationship between object. examples: Semantic nets, Conceptual graphs.
4. Structured Scheme
Structured schemes extend networked representation by displaying each node in the graph as a complex data structure. example: scripts, frames.
Parameters of Good knowledge Representation Scheme
Some important parameters of good knowledge representation schemes are given below:
1. Ease of representation: The ease with which a problem can be solved depends upon knowledge representation methods.
2. Granularity of representation: Granularity of knowledge representation can affect its usefulness, that is, how detailed the knowledge need to be represented.
3. Expressiveness: An expressive representation scheme will be able to handle different type and levels of granularity of the knowledge.
4. Explicitness: A good knowledge representation scheme to be able to provide an explanation of its inference and allow justification of its reasoning.
5. Efficiency: The scheme should not only support inference of new knowledge from old but must do so efficiently in order for new knowledge to be used.
6. Effectiveness: In order to scheme be effective, it must provide a means of inferring new knowledge from old.
This article is contributed by Ram Kripal. If you like eLgo Academy and would like to contribute, you can mail your article to email@example.com. See your article appearing on the eLgo Academy page and help others. Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.