Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
Case-based reasoning
Petri Net Theory and the Modeling of Systems
Petri Net Theory and the Modeling of Systems
The Case for Graph-Structured Representations
ICCBR '97 Proceedings of the Second International Conference on Case-Based Reasoning Research and Development
The Case for Graph-Structured Representations
ICCBR '97 Proceedings of the Second International Conference on Case-Based Reasoning Research and Development
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In this paper, a case-based intelligent tutoring system (CBITS) using conceptual graphs to represent the cases is described. Among others, two core issues to be addressed by CBITS developers are indexing and how learning activities can be constructed from the cases. Addressing the former, the authors discovered that the minimum common generalization of a set of graphs is a powerful means of embedding different tutorial primitives into the cases. This approach provides an extremely rich indexing vocabulary for the cases and relieves the developers from speculative assignment of indexes. For constructing learning activities an operational semantics for the case graphs is defined and with this semantics the instructor can reason about the graph structure and provide intelligent guidance to the students in exploring the case contents. Newtonian mechanics is the testing domain of the proposal but its underlying methodology should be equally applicable to other subject domains.