Knowledge Representation: A Conceptual Modeling Approach
Abstract
Substantial work in knowledge engineering has focused on eliciting knowledge and representing it in a computational form. However, before elicited knowledge can be represented, it must be integrated and transformed so the knowledge engineer can understand it. This research identifies the need to separate knowledge representation into human comprehension and computational reasoning and shows that this will lead to better knowledge representation. Modeling of human comprehension is called conceptual knowledge representation. The Conceptual Knowledge Representation Scheme is developed and validated by conducting a combined qualitative/quantitative repeated-measures experiment comparing the Conceptual Knowledge Representation Scheme to two computation-oriented ones. The results demonstrate that the Conceptual Knowledge Representation Scheme better facilitates human comprehension than existing representation schemes. Four principles of the Conceptual Knowledge Representation Scheme emerge that help to attain effective knowledge representation. These are: (1) a focus on human comprehension only, (2) design around natural language, (3) addition of constructs common in the domain, and (4) constructs for representing abstract versions of detailed concepts.
Recommended Citation
Chua, C. E., Storey, V. C., & Chiang, R. H. (2012). Knowledge Representation: A Conceptual Modeling Approach. Journal of Database Management, 23(1), pp. 1-30. IGI Global.
The definitive version is available at https://doi.org/10.4018/jdm.2012010101
Department(s)
Business and Information Technology
Keywords and Phrases
Conceptual Modeling; Human Comprehension; Knowledge Representation; Ontology; Qualitative Analysis
International Standard Serial Number (ISSN)
1063-8016; 1533-8010
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2012 IGI Global, All rights reserved.
Publication Date
01 Jan 2012