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Capturing Evolutional Knowledge Using Time Interval Tracing
Author(s) -
Shun-Chieh Lin,
Chia-Wen Teng,
ShianShyong Tseng
Publication year - 2007
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2007.p0373
Subject(s) - computer science , domain knowledge , bottleneck , knowledge base , knowledge acquisition , knowledge based systems , domain (mathematical analysis) , open knowledge base connectivity , ontology , knowledge extraction , knowledge engineering , tracing , knowledge integration , artificial intelligence , knowledge management , personal knowledge management , organizational learning , programming language , mathematical analysis , philosophy , mathematics , epistemology , embedded system
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.

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