Seamless Structured Knowledge Acquisition

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Author(s): Päivikki Parpola (Helsinki University of Technology, Finland)
Copyright: 2009
Pages: 7
Source title: Encyclopedia of Data Warehousing and Mining, Second Edition
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-60566-010-3.ch262

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Abstract

Some parts of this text, namely “Co-operative Building, Adaptation, and Evolution of Abstract Models of a KB” and most subsections in “Performing Reasoning in SOOKAT According to a KB”, have appeared in an article (DOI:10.1007/s10115-004-0181-6) published in the ‘Knowledge And Information Systems’ journal (Parpola, 2004). A knowledge base (KB) contains data and instructions for using it (e.g., as a rule base). A KB containing knowledge possessed by experts can be used in an expert system. It can solve problems requiring expert knowledge, explain its decisions and deal with uncertainty. An expert system can be used as a basis for a larger system, called a knowledge-based system (KBS). Knowledge acquisition (KA) that is the development and maintenance of KBs, (e.g. an expert system), can be divided into several phases, performed sequentially and iteratively. Some phases may be performed in parallel with other phases. The most commonly recognised phases are requirements definition, analysis, design, and implementation. Disintegration, or the gap between phases of development, especially between abstract and executable descriptions, was recognised during the early stages of KA (Marcus, 1988a; Motta, Rajan and Eisenstadt, 1988). It complicates the development of KBs and hinders traceability between parts of abstract and executable descriptions.

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