In educational context, ontologies can be applied to solve a variety of complex problems such as knowledge representation in intelligent systems, knowledge sharing, application reuse, annotation and search for learning objects, personalization of learning content, among many other challenges [36].
However, existing CBR systems lack semantic understanding, which is important for intelligent knowledge retrieval in design support system.
We unveil the relevance of transient memory that underlines the utility of the above mechanisms for intelligent knowledge management in artificial sensorimotor systems.
In order to facilitate the use of these TRIZ models and knowledge sources, an intelligent knowledge management system – IngeniousTRIZ was developed in this research.
The knowledge is represented through ontology as an artificial intelligent knowledge representation method [7].
Applying domain knowledge in intelligent systems is not new, but applying general knowledge to support business decision making is a possible way to obtain an edge over competitors.
When intelligent inference is making in intelligent expert system, special knowledge and rules and parameters relevant will be extracted from distributed knowledge base and data base.
Ideas and concepts of distributed systems, artificial intelligence, and soft computing are merged into a unique architecture to provide the cooperation, flexibility, and adaptability required by knowledge processing in intelligent control systems.
New approaches are needed that could move us towards developing effective applicable intelligent systems for problem solving and decision making, One of the main efforts in intelligent systems development is focused on knowledge and information management which is regarded as the crucial issue in smart decision making support.
The resulting knowledge structures facilitate reasoning in intelligent systems.
