JACIII Vol.11 No.4 pp. 373-380
doi: 10.20965/jaciii.2007.p0373


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

April 4, 2006
August 8, 2006
April 20, 2007
expert system, knowledge acquisition, EMCUD, VODKA, grid evolution
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.
Cite this article as:
S. Lin, C. Teng, and S. Tseng, “Capturing Evolutional Knowledge Using Time Interval Tracing,” J. Adv. Comput. Intell. Intell. Inform., Vol.11 No.4, pp. 373-380, 2007.
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