Journal Article
© Aug 2007 Volume 5 Issue 3, Editor: Charles Despres, pp257 - 347
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Abstract
The major bottlenecks in expert system development lie within the processes of eliciting and representing knowledge. Knowledge representation schemes combine data structures, and interpretative procedures that enable the extraction of the knowledge embedded in the data structures. A broad spectrum of knowledge types need to be represented, but available representation techniques are not optimum systems since they vary in level of expressiveness and power. Knowledge demands more than the conventional representation structures used for databases and information. This is because information is derived from processing, refining and analysing raw data. The extra refinement, analysis and addition of heuristics to information converts it to knowledge. This paper discusses the major issues in the quest for an efficient knowledge representation technique and assesses the performance and level of usefulness of some of the most successful approaches in knowledge representation.
Keywords: knowledge representation, knowledgebase, production rule, semantic nets, frames, propositional logic, predicate logic, fuzzy logic
Journal Issue
Volume 5 Issue 3 / Jul 2007
pp257‑347
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Keywords: architectures for knowledge management systems, business school, case based reasoning, communities of practice, customer relationship management, decision making, discovery query, expert, failure factors, frames, fuzzy logic, Heidegger, info-culture, info-structure, infrastructure, knowledge acquisition, knowledge adaptation, knowledge communication, knowledge dialogues, knowledge dissemination, knowledge generation, knowledge management practices, knowledge management systems, knowledge media, knowledge representation, knowledge transfer, knowledge utilization, knowledgebase, learning organization, ontology, organizational knowledge, popper, predicate logic, production rule, propositional logic, ranking semantic relations, relation robustness, relationship search, semantic associations search, semantic nets, semantic web, social capital, structuration theory, success factors of KM, validation
Journal Issue
Volume 5 Issue 4 / Dec 2007
pp347‑550
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Keywords: architectures for knowledge management systems, business school, case based reasoning, communities of practice, customer relationship management, decision making, discovery query, expert, failure factors, frames, fuzzy logic, Heidegger, info-culture, info-structure, infrastructure, knowledge acquisition, knowledge adaptation, knowledge communication, knowledge dialogues, knowledge dissemination, knowledge generation, knowledge management practices, knowledge management systems, knowledge media, knowledge representation, knowledge transfer, knowledge utilization, knowledgebase, learning organization, ontology, organizational knowledge, popper, predicate logic, production rule, propositional logic, ranking semantic relations, relation robustness, relationship search, semantic associations search, semantic nets, semantic web, social capital, structuration theory, success factors of KM, validation
Journal Issue
Volume 6 Issue 1 / Jul 2008
pp1‑74
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Keywords: architectures for knowledge management systems, business school, case based reasoning, communities of practice, customer relationship management, decision making, discovery query, expert, failure factors, frames, fuzzy logic, Heidegger, info-culture, info-structure, infrastructure, knowledge acquisition, knowledge adaptation, knowledge communication, knowledge dialogues, knowledge dissemination, knowledge generation, knowledge management practices, knowledge management systems, knowledge media, knowledge representation, knowledge transfer, knowledge utilization, knowledgebase, learning organization, ontology, organizational knowledge, popper, predicate logic, production rule, propositional logic, ranking semantic relations, relation robustness, relationship search, semantic associations search, semantic nets, semantic web, social capital, structuration theory, success factors of KM, validation
