Knowledge acquisition is the gathering or collecting knowledge from various sources. It is the process of adding new knowledge to a knowledge base and refining or improving knowledge that was previously acquired. Acquisition is the process of expanding the capabilities of a system or improving its performance at some specified task. So it is the goal oriented creation and refinement of knowledge. Acquired knowledge may consist of facts, rules, concepts, procedures, heuristics, formulas, relationships, statistics or any other useful information. Source of these knowledges may be experts in the domain of interest, text books, technical papers, database reports, journals and the environments. The knowledge acquisition is a continuous process and is spread over entire lifetime. Example of knowledge acquisition is machine learning. It may be process of autonomous knowledge creation or refinements through the use of computer programs. The newly acquired knowledge should be integrated with existing knowledge in some meaningful way. The knowledge should be accurate, non-redundant, consistent and fairly complete. Knowledge acquisition supports the activities like entering the knowledge and maintaining knowledge base. The knowledge acquisition process also sets dynamic data structures for existing knowledge to refine the knowledge.
The role of knowledge engineer is also very important with respect to develop the refinements of knowledge. Knowledge engineers may be the professionals who elicit knowledge from experts. They integrate knowledge from various sources like creates and edits code, operates the various interactive tools, build the knowledge base etc.
Figure Knowledge Engineer’s Roles in Interactive Knowledge Acquisition
Knowledge Acquisition Techniques
Many techniques have been developed to deduce knowledge from an expert. They are termed as knowledge acquisition techniques. They are:
a) Diagram Based Techniques
b) Matrix Based Techniques
c) Hierarchy-Generation Techniques
d) Protocol Analysis Techniques
e) Protocol Generation Techniques
f) Sorting Techniques
In diagram based techniques the generation and use of concept maps, event diagrams and process maps. This technique captures the features like “why, whe n, who, how and where”. The matrix based techniques involve the construction of grids indicating such things as problems encountered against possible solutions. Hierarchical techniques are used to build hierarchical structures like trees. Protocol analysis technique is used to identify the type of knowledge like goals, decisions, relationships etc. The protocol generation techniques include various types of interviews like structured, semi-structured and unstructured.
The most common knowledge acquisition technique is face-to-face interview. Interview is a very important technique which must be planned carefully. The results of an interview must be verified and validated. Some common variations of an unstructured interview are talk through, teach through and read through. The knowledge engineer slowly learns about the problem. Then can build a representation of the knowledge. In unstructured interviews, seldom provides complete or well-organized descriptions of cognitive processes because the domains are generally complex. The experts usually find it very difficult to express some more important knowledge. Data acquired are often unrelated, exists at varying levels of complexity, and are difficult for the knowledge engineer to review, interpret and integrate. But on the other hand structured interviews are systematic goal oriented process. It forces an organized communication between the knowledge engineer and the expert. In structured interview, inter personal communication and analytical skills are important.
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