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The application of fuzzy Petri Nets to the development of intelligent systems has received an increasing attention recently. However, the fuzzy production rules are rather limited if the determination of certainty factor for each proposition is subjective. Unfortunately, this is the case for many existing fuzzy Petri nets. This paper proposes a generalized associative Petri net model with associative degree and knowledge representation of a rule-based system. Based on the generalized associative Petri net model, an efficient reasoning algorithm is proposed. The ontology mapping and the associative reasoning algorithm are described formally in details. An example of malicious email reasoning is also included as an illustration.
Ontology, Petri net, Reasoning, Association rule, Data mining

B. Lin, H. Chiang and D. Shih, "A Generalized Associative Petri Net for Reasoning," in IEEE Transactions on Knowledge & Data Engineering, vol. 19, no. , pp. 1241-1251, 2007.
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