||Due to popularize of social networks and instant messaging applications, mobile usage has grown at an unprecedented pace and has become the most efficient way for people to connect. As a result, sparked a new type of service through automated conversational agents, Chatbot. Lowering costs by disseminating information through predesigned processes has become a hot industry research topic. A chatbot is an automated response system through texts or voice messaging, achieved by artificial learning to simulate human communication.|
This research based on Python for program development utilizes open source web framework Django, Microsoft’s QnA Maker and LUIS for text recognition to design chatbot. Previous chatbot developments require proficient natural language cognition and training through massive language information to reach effective results. This system, however, focuses on minimizing information training time to achieve quicker implementation of in-school information chatbot system; by gathering school’s FAQ pages and threads, automated collection and training will strengthen chatbot’s work processes for effective services.
Other than developing chatbot services, this research also suggests managing protocols, including chat logs, inquiring session logs, service quality feedbacks, transference to person and rating feedbacks. Through simplified management and training, visualized monitoring tools, data analysis, backend operator can grasp the effectiveness of interactions in real-time, making sure quality fits its entirety. Most importantly, alleviate servicing staff’s workload, accumulate experience and data, resulting in improvement of the service quality that reaches to 12.63%.
|| Cai Shushan, and Xue Xiaodi, ‘‘Artificial Intelligence and Human Intelligence：A view on Human-Computer Competition from the Five-Level Theory of Cognitive Science,’’Journal of Peking University(Philosophy and Social Sciences), Vol53 No.4, Jul 2016.|
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