| Summary: | 碩士 === 國立臺灣科技大學 === 資訊工程系 === 106 === In many sightseeing areas or national parks, there may not always be enough service staff during holidays. This causes the waiting time of tourists to become longer and the quality of the service staff's answer to decline, resulting in problems like reduction in evaluation. Our goal is to develop an question answering system to solve the problem of understaffing by utilizing the frequently asked questions in those sightseeing area or national park.
In this paper, via the relationship between the question and the answer in each Q&A pair, the Q&A pairs are clustered into many groups, in order to find the keywords in those questions which have the same purpose but asked in different ways, so that the user does not need to pick the keywords on his own. Then, we design a question generation method to generate more questions using the imported Q&A pairs; this can help our system dealing with more diverse questions. Finally, we use the visitor inquiry record to teach the machine how to answer those questions that was answered poorly, thereby strengthening the system's answering ability.
Our Q&A system has several excellent experimental results. The system can generate keywords in those questions which have the same purpose but asked in different ways. When facing a question from a visitor, the system can give the answer of the most relevant question, to assist the service staff in explaining, alleviating the problem of understaffing. In most cases, the user only needs to import the collected Q&A pair into the system, so that the system can learn the keywords of the questions among different purposes. After that, all you need to do is to add new answers for the questions from the visitors, and let the system learn, that will enhance the answering ability of the system.
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