expert system

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Expert system

A software system designed to emulate the processes and procedures conducted by humans in particular areas of expertise, thereby automating decision-making processes.

expert system

a COMPUTER programme which simulates the problem-solving and decision-making behaviour of a technical expert in a particular field such as engineering and medicine. Like human technical experts, expert systems are able to learn from experience and restructure their knowledge in order to improve their future problem-solving.
References in periodicals archive ?
(wenke@ontoprise.de), is a senior software developer and knowledge engineer at Ontoprise GmbH, Karlsruhe.
Although interactive machine learning assumes that end users (domain experts) directly interact with machine learning algorithms, we shall assume that a knowledge engineer acts as an intermediate between a domain expert and the algorithm, since some of the suggested steps in this section would be difficult to implement automatically.
The knowledge engineer can decide on which method to use depending on the study domain, amount of knowledge needed, and the efforts required to analyze the collected information (Osuagwu, Okafor 2010).
Acquiring knowledge is an important stage in creating expert systems: it is achieved by the knowledge engineer who needs to have a good knowledge of the methods of representing knowledge, methods provided by knowledge engineering such as: the method based on production rules; the method based on semantic nets; the frame-based method; the method based on logical models (propositional logic, the logic of predicates of the 2nd order); the method based on probabilistic logic (Bayesian logic); the method based on fuzzy set and logic (Moise, 2007).
By being a "good interviewer," this should enable someone to not only be useful as a knowledge engineer, but also helpful in other professions (like news reporting, medical diagnosis, etc.) as well.
The knowledge engineering process requires that a technician, usually called a knowledge engineer, interviews and observes the expert in his or her area of expertise.
The knowledge must be available from an expert and the expert must have time to work with a knowledge engineer. The interpersonal interaction between the expert and the knowledge engineer is critical.
The knowledge engineer usually obtains this knowledge through direct interaction with the expert.
During the second state, conceptualization, the expert and knowledge engineer discuss and determine the key concepts, data relationships and information-flow characteristics that describe the problem-solving process.
This is the job of the knowledge engineer, who is the link between the software developer and the end user.
Custom development involves finding an expert in the given area, using the services of a knowledge engineer to extract the expertise and heuristics from this person, quantifying this information in a computer program, and finally, validating and testing the program.
In majority of existing approaches an additional role of knowledge engineer is required for mediation between actual knowledge that business users possess and ontology engineers who encode knowledge in one of selected formalisms.
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