Paper:
Language: English:

Capturing Evolutional Knowledge Using Time Interval Tracing

Shun-Chieh Lin^, Chia-Wen Teng^, and Shian-Shyong Tseng^*,**

^*Department of Computer Science, National Chiao Tung University, 1001, Ta-hsueh Rd., Hsinchu, Taiwan
^**Department of Info. Sci. & App., Asia University, 500, Liu-Feng Rd., Wufeng, Taichung, Taiwan

Received: April 4, 2006

Accepted: August 8, 2006

Keywords: expert system, knowledge acquisition, EMCUD, VODKA, grid evolution

Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.11, No.4 pp. 373-380, 2007

Abstract

Knowledge acquisition is a critical bottleneck in building a knowledge-based system. Much research and many tools have been developed to acquire domain knowledge with embedded rules that may be ignored in constructing the initial prototype. Due to different backgrounds and dynamic knowledge changing over time, domain knowledge constructed at one time may be degraded at any time thereafter. Here, we propose knowledge acquisition, called enhanced embedded meaning capturing under uncertainty deciding (enhanced EMCUD), which constructs a domain ontology and traces information over time to efficiently update time-related domain knowledge based on the current environment. We enrich the knowledge base and ease the construction of domain knowledge that changes with times and the environment.

[Notice]
* "Preview" is the first 2 pages of the article. You don't need the registration.
* To read the PDF file you will then need to download and install the Adobe Reader.
Adobe Reader is free and available for download here: