| Summary: | 碩士 === 中原大學 === 資訊管理研究所 === 101 === Concerning about food safety problems in Taiwan and overseas in recent years, the significant event continues to happen one by one. From the 2008's melamine poison milk event, in 2011 the plasticizer storm and government allows U.S. beef ractopamine residue amounts of controversy in 2012. Since 2013’s poisonous starch events, etc., those events are all caused people panic and worry. The problem for upstream is that they do not control the flow of industrial materials. Midstream problems are food additives firms registered ineffective, but Midstream has not informed those problems to downstream and health authorities. The units of government authorities have no way to check up on afterwards raw materials, semi-finished products flow and they can only take a negative way to check. Highlighting the big problems in control of raw materials in Taiwan with the phenomenon of posting loopholes, and even afterwards there is no way to control the flow of raw materials identified. Therefore, production resumes and supply chain become worthy of further discussion.
In this study, the ontology model of the development of production resumes should resume with recent food safety incidents of illegal use of industrial additives "maleic acid" as experimental cases. This relationship between the food industry in the production and marketing chain classification from downstream to upstream is divided into four layers, build company information, product information and tracking method ontology. The former two define the logical relationship between knowledge sources; The latter are designed to track queries applications. Through knowledge modeling and expression, semantic rules are developed and establish the relationship between companies, products, and tracking methods. The result of tracking methods corollary to achieve the best "source management" philosophy.
The use of inference mechanisms enforcing rules, check the value of the attribute content. The test results are the same with artificial simulations consistent. Moreover, after checking, it is correct to re-derive knowledge structures by verification system another two performance index ─expansion and trustworthiness. And we also change the content of a number of instances to observe whether the inference mechanism to rebuild the entire structure of knowledge which can generate the knowledge chain updates.
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