How to Recommend the Best Representation Model for Problem-Solving

Knowledge is a representation of truth and facts, enabling the integration of new experiences and information through language comprehension. It is represented using Adaptive Control of Thought (ACTR) and the connectionist model. Knowledge organization is a semantic network with labeled relations to conceptual nodes. An Ontology-based framework is built for the Language and Organization of Knowledge in the human brain. This project aims to conduct surveys for graduation levels and analyze factors affecting knowledge skills in problem-solving. A semantic web approach for the Connectivism model is created, and Semantic Web Rule Language (SWRL) is applied to generate inference rules. Knowledge is retrieved using SPARQL, forming an intelligent system based on the inference engine.