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Obtaining Exhaustive Answer Set for QA-based Inquiry System using Customer Behavior and Service Function Modeling

机译:使用客户行为和服务功能建模获取基于Q&A的查询系统的详尽答案设置

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When customers are interested in a service or intend to buy it, they sometimes have questions on that service. In this study, we considered an inquiry system in which customers ask questions on a specific service and obtain correct information on the service. For such an inquiry system, a question-answering (Q&A) technology is needed. Many programming modules for such a technology have been developed and can be easily used for system development. In many Q&A technologies, machine-learning techniques are involved, and we need to prepare training data consisting of pairs of an answer and assumed questions. For training-data preparation, an answer set for a service should be defined as the first step and the answer set should cover all the information on the service that customers may ask about. By using a customer-behavior model and introducing a service-function model, we propose a method of effectively collecting knowledge information for an answer set on a service. Through a case study, we show that we can collect exhaustive knowledge information for an answer set with our method compared to the case in which domain experts collect knowledge information in their own way. For an actual project, we also considered an actual inquiry-system-development project, with training data obtained with the proposed method, and showed that the system covers almost all the information on the service that customers may ask after a user test.
机译:当客户对服务或打算购买的兴趣时,他们有时对该服务有任何疑问。在这项研究中,我们考虑了一个询问系统,其中客户在特定服务上提出疑问并获得有关该服务的正确信息。对于这样的询问系统,需要问答(Q&A)技术。已经开发出许多用于这种技术的编程模块,可以轻松用于系统开发。在许多Q&A技术中,涉及机器学习技术,我们需要准备由对答案的对和假设问题组成的培训数据。对于培训数据准备,应定义为服务的答案设置为第一步,答案集应涵盖客户可能询问的服务的所有信息。通过使用客户行为模型并引入服务功能模型,我们提出了一种有效地收集在服务上设置的答案知识信息的方法。通过案例研究,我们表明,与域专家以自己的方式收集知识信息收集知识信息的情况相比,我们可以为使用我们的方法提供详尽的知识信息。对于实际项目,我们还考虑了一个实际的查询系统开发项目,通过提出的方法获得了培训数据,并显示系统几乎涵盖了客户在用户测试之后可能会询问的服务的所有信息。

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