| Summary: | 碩士 === 大同大學 === 資訊工程學系(所) === 97 === Taiwanese enterprises were forced to relocate their manufacturing bases to regions where provide cheaper labor such as the neighboring areas in China and other Southeast Asian countries. To improve resource utilization and to cut service-resolution times, we have to train local area employees to maintain information system and train them to be call center contact window. According to the high departee rate of employees, it is very difficult to train new member to realize the whole system within a short time. So, how to let call center IT members promptly understand the nature and severity of end-users queries become the top problem to be solved.
In this thesis, the training data were collected from a company in 2007~2008. By utilizing the learning capability of back-propagation neural networks, we can predict the cause of the reason. We also apply the decision tree method to extracting the more influential factor for classification. The extracted factors are then become the inputs of back-propagation network to classify end-user queries and problems. Not only the simulation results are provided, but also a detailed discussion about the false prediction is given. The present work can be used as a reference for analyzing the reason of end-user queries and help call center members to solve the problem by self service.
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