A new Methodology of Mining Cognitive Maps

Cognitive map (CM) is a new intelligent method. Compared either experts system and neural networks, it has several desirable advantages such as: it is relative easy to use for representing structured knowledge, and the inference can be computed by numeric matrix operation instead of explicit IF/THEN rules. However, in order to exhibit these advantages about CM, the first step is that the corrected CMs must be obtained. Traditional approaches for obtaining the CMs, including questionnaire method, brainstorming method and sample learning method, mainly rely on experience of domain experts. Because these methods put much emphasis on the subjective factors, neglect the objective data resources, they always lose some information. Therefore, this paper proposes a new methodology of mining the CMs based on data resource, which mainly includes database preprocessing technology, optimization algorithm for weight coefficients and simplification strategy of CMs. The experimental research based on a finance database is done and the results show that: the new method can mine all possible relationship among all nodes to form the CMs, and can also simplify it according to the significant degree of relationships; the CMs mined by the new method has more information than the CMs obtained by traditional approaches.