首页> 外文期刊>Informatica: An International Journal of Computing and Informatics >Automated Self-learning Chatbot Initially Build as a FAQs Database Information Retrieval System: Multi-level and Intelligent Universal Virtual Front-office Implementing Neural Network
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Automated Self-learning Chatbot Initially Build as a FAQs Database Information Retrieval System: Multi-level and Intelligent Universal Virtual Front-office Implementing Neural Network

机译:自动化的自学聊天机器人最初构建为常见问题数据库信息检索系统:多层智能通用虚拟前台实现神经网络

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In this paper we propose a novel approach of an automatic creation of a chatbot exploiting only a questions-answers archive. The described model is not bound to a particular context or language, and it allows to initially retrieve information from a FAQs database using natural language, by allowing successively the automation of customer support services for the optimization of human resources thus implementing a self-learning chatbot system. We also propose a solution based on dynamical information system capable of exploiting the potential of the proposed model in a universal virtual front-office, including the statistics and tests necessary to validate the solution, and a comparison between neural network and AIML results.
机译:在本文中,我们提出了一种新颖的自动创建聊天机器人的方法,该聊天机器人仅利用问题-答案档案。所描述的模型不受特定上下文或语言的束缚,并且通过先后允许客户支持服务自动化以优化人力资源,从而实现自学聊天机器人,它允许使用自然语言从FAQs数据库中最初检索信息。系统。我们还提出了一种基于动态信息系统的解决方案,该解决方案能够在通用虚拟前台中利用提出的模型的潜力,包括验证解决方案所需的统计数据和测试,以及神经网络和AIML结果之间的比较。

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