Using case-based reasoning mechanisms to construct a computer problem diagnosis expert system–A case study of company
|關鍵字:||專家系統;案例式推理;準確率與召回率;Expert Systems;Case Based Reasoning;Precision and recall rate|
In addition to the company's network management in checking whether the system faces abnormal occurences, network administors are responsible for solving computer and network problems. So building a system management tool to deal with these issues in the shortest possible time is the first priproty and urgency of the work. Based on case-based reasoning, this research uses clustering methods combined with article vector similarity weights for cnducting cluster analysis and utlizes Bayesian classification model to train and test dataset and calculate the accuracy and recall value. The system records a cumulative knowledge base according to the problem occuring the the past years and uses event processing system to effectively control the flow of computer problems, which are addressed as references for the future. In this study, the recall rate and authentication methods are used as indicators to assess the accuracy of the experimental results. It is shown that the recall rate and the accuracy rate are more than 95 percentage which has reached a certain degree of reliability. It is expexted that the system will help enterprise information systems to handle unusual problems. In the future, more diverse solutions can be developed for system administrators to enhance the overall competitiveness.