Knowledge engineering involves collecting information for use in knowledge-based computing systems that can solve problems or answer questions without human help. The process is manpower-intensive, with the longest step being knowledge acquisition. Techniques such as protocol generation and sorting are used to gather information from experts.
Knowledge engineering is the task of collecting and inputting information for use in knowledge-based computing systems. These systems can solve problems or answer questions without the help of a human expert. Knowledge engineers use a variety of tailored knowledge acquisition techniques to gather specific types of information.
The field of knowledge engineering developed when computer memories became large enough to hold massive amounts of information, around 1970. This caused a shift in artificial intelligence (AI) technology. In addition to creating AI software that can solve problems and use logic, programmers have been able to give AI a huge database of information to draw from.
Knowledge engineering is a multi-step, manpower-intensive process. First, the knowledge engineer is presented with a problem. For example, the issue might be to enable people to find out what their medical symptoms mean without going to the doctor. The engineer then creates a system that can do this: for example, a computer program that takes symptoms as input and outputs a list of conditions or diseases that might be exhibiting those symptoms.
Then the engineer has to collect the necessary information. The engineer might talk to doctors or read medical texts to find information about diseases and symptoms. Once all the information is gathered and organized, the programmers create the system. The engineer enters the data. The final step in knowledge engineering is testing the system to ensure it provides accurate answers.
The longest and probably most important step in the knowledge engineering process is knowledge acquisition. Most of the knowledge needed to create a knowledge-based system resides in the brains of the experts. These experts are usually busy people. The challenge facing the knowledge engineer is how to get this information as quickly and efficiently as possible.
Another challenge is how to gather the information that the expert knows implicitly. For example, a doctor may not be able to describe the sound of an asthmatic lung. He only knows it when he hears it.
Knowledge engineers have developed a number of knowledge acquisition techniques to help them gather information. These include protocol generation techniques, limited information techniques, and matrix-based techniques. Techniques are chosen based on the type of knowledge needed.
For example, if an engineer needed information about the steps a doctor should take to make a diagnosis, they could simply interview the doctor. If, however, the information the engineer was looking for was the kind of information the doctor knows about but has difficulty putting into words, he might employ a sorting technique. One sorting technique requires the expert to sort cards with words on them into piles and then name the categories he has used. This allows the engineer to understand how the expert thinks about the information.
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