Knowledge engineering

Knowledge engineering is the field of artificial intelligence associated with the development of expert systems and knowledge bases. Studies methods and means of extracting, presenting, structuring and using knowledge.

Currently, it also involves the construction and maintenance of such systems. It is also closely related to software engineering, and is used in many information studies, such as artificial intelligence research including databases, data collection, expert systems, decision support systems, and geographic information systems. Knowledge engineering is also associated with mathematical logic , also used in various scientific disciplines, for example, in sociology where people are “experimental”, and research goals are understanding how human logic works in relation to social relationships.

An example of the action of a system based on knowledge engineering:

• Task review
• Request to databases on the task
• Entering and structuring information received (IPK model)
• Creating a database of structured information
• Testing the information received
• Making adjustments and the evolution of the system.

Being an art rather than a purely engineering task, IZ does not have much practical use. The knowledge engineering subsection is knowledge engineering, suitable for the development of artificial intelligence.

Since the mid-1980s, several principles, methods, and tools have emerged in knowledge engineering that have facilitated the process of obtaining and working with knowledge. Here are some key ones: There are all sorts of types of knowledge and specific methods and techniques should be used to work with them. There are various types of experts and experience. To work with them should be used certain methods and techniques. There are different ways to provide, use, understand and work with knowledge can help rethink and use existing knowledge in new ways. Knowledge engineering uses knowledge structuring methods to speed up the process of acquiring and working with knowledge.