| Summary: | 碩士 === 國立臺南大學 === 資訊工程學系碩士班 === 97 === Nowadays, it is an information explosion age. People, however, often get hundreds of thousands of data when using a keyword to search for the wanted information from the Internet. Even so, sometimes the displayed data are not the ones that people need. Therefore, with such some data, people still need to transform them to information, and further to knowledge to store into the brains. In this thesis, a study and construction on ontology-based intelligent semantic web is proposed and applied to intelligent healthcare agent as well as a semantic network flow monitoring system. Today, how to eat healthily to stay away from cardiovascular diseases is one of the most important topics for modern people. Based on the ontology, the fuzzy inference, and the Ant Colony Optimization (ACO), the proposed intelligent healthcare agent has an ability to find the personal healthy food route and then to display the recommended food route on the Google Map. Next, owning to the popularity of the Internet, the users’ abnormal usages such as downloading the mass pockets in a short time are often one of the reasons to affect the quality of the network and even to cause the Internet to crash. Additionally, the unexpected environment variances are also one of the reasons. In this thesis, a semantic network flow monitoring system is proposed to monitor the campus network flow of the National University of Tainan, Taiwan. Additionally, it uses Fuzzy Markup Language (FML) to describe the knowledge base and rule base. Based on the ontology and the fuzzy inference, it makes network administrators much easier and quicker to understand the loading condition of the network flow. From the experimental results, the proposed approaches are feasible for the personal food route recommendation and the network flow monitoring. The proposed methods not only alleviate the workload of the domain experts, but also increase the level of healthy diet and escalate the stability of the network flow.
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