Concept
Knowledge acquisition
Overview
Knowledge acquisition is the process used to define the rules and ontologies required for a knowledge-based system. The phrase was first used in conjunction with expert systems to describe the initial tasks associated with developing an expert system, namely finding and interviewing domain experts and capturing their knowledge via rules, objects, and frame-based ontologies.
Expert systems were one of the first successful applications of artificial intelligence technology to real world business problems. Researchers at Stanford and other AI laboratories worked with doctors and other highly skilled experts to develop systems that could automate complex tasks such as medical diagnosis. Until this point computers had mostly been used to automate highly data intensive tasks but not for complex reasoning. Technologies such as inference engines allowed developers for the first time to tackle more complex problems.
As expert systems scaled up from demonstration prototypes to industrial strength applications it was soon realized that the acquisition of domain expert knowledge was one of if not the most critical task in the knowledge engineering process. This knowledge acquisition process became an intense area of research on its own. One of the earlier works on the topic used Batesonian theories of learning to guide the process.
One approach to knowledge acquisition investigated was to use natural language parsing and generation to facilitate knowledge acquisition. Natural language parsing could be performed on manuals and other expert documents and an initial first pass at the rules and objects could be developed automatically. Text generation was also extremely useful in generating explanations for system behavior. This greatly facilitated the development and maintenance of expert systems.
A more recent approach to knowledge acquisition is a re-use based approach. Knowledge can be developed in ontologies that conform to standards such as the Web Ontology Language (OWL). In this way knowledge can be standardized and shared across a broad community of knowledge workers. One example domain where this approach has been successful is bioinformatics.
Overview adapted from Wikipedia (CC BY-SA 4.0; see the article history for authors).
Possible passages
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Now Knowledge is a conception concerning universals and Necessary matter, and there are of course certain First Principles in all trains of demonstrative reasoning (that is of all Knowledge because this is connected with reasoning): that faculty, then, which takes in the first principles of that which comes under the range of Knowledge, cannot be either Knowledge, or Art, or Practical Wisdom: not Knowledge, because…
Aristotle, The Nicomachean ethics of Aristotle
Close in meaning to Knowledge acquisition; the term itself is not named.
Scientific induction is an attempt to regularise the above process, which we may call “physiological induction”. It is obvious that, as practised by animals, infants, and savages, physiological induction is a frequent source of error. There is Dr.
Bertrand Russell, Philosophy
Close in meaning to Knowledge acquisition; the term itself is not named.
Of The Deductive Method. § 1. The mode of investigation which, from the proved inapplicability of direct methods of observation and experiment, remains to us as the main source of the knowledge we possess or can acquire respecting the conditions and laws of recurrence, of the more complex phenomena, is called, in its most general expression, the Deductive Method; and consists of three operations: the first, one of…
John Stuart Mill, A System of Logic, Ratiocinative and Inductive
States what Knowledge acquisition is.
Related ideas
Place in the tradition
Part of Fallibilism.