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An E-Commerce Customer Service Robot Based on Intention Recognition Model

机译:基于意图识别模型的电子商务客户服务机器人

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摘要

There are three defects for providing human-labor customer services in e-commerce operations: high costs of human labors, staff turnover, and lack of service quality assurance. Breakthroughs made in artificial intelligence, natural language processing and related fields make it possible to replace human labors with online artificial intelligent robots to provide the e-commerce customer service, which indicates the online robots are the future of e-commerce customer services. However, most of the current robots are designed to reply with knowledge matching the key words in question sentences from the database, rarely involving in research on customer intentions that are key factors influencing user experience and online sales. In this research, an intention recognizing model was proposed to obtain intentions of e-commerce consumers by computing the strengths of candidate intention nodes in the intention graph, which was used to describe relations between different goods that could be the intentional targets of e-commerce consumers. The proposed robot was constructed based on the intention recognizing model to identify intentions of consumers and use the located knowledge combined with the AIML based sentence composition template to produce the response sentences for consumers. At last, the proposed robot was evaluated using F3 and ROUGE metrics by comparing with a keyword matching robot. And the evaluation results proved the validity of the proposed robot.
机译:在电子商务运营中提供人工服务的客户存在三个缺陷:人工成本高,人员流动以及缺乏服务质量保证。人工智能,自然语言处理及相关领域的突破使得可以用在线人工智能机器人代替人工来提供电子商务客户服务,这表明在线机器人是电子商务客户服务的未来。但是,当前大多数机器人被设计为使用与数据库中疑问句中的关键字相匹配的知识进行回复,很少涉及对客户意图的研究,而客户意图是影响用户体验和在线销售的关键因素。本研究提出了一种意向识别模型,通过计算意向图中候选意向节点的强度来获得电子商务消费者的意向,该意向识别模型用于描述可能成为电子商务意向目标的不同商品之间的关系。消费者。基于意图识别模型构造提出的机器人,以识别消费者的意图,并将定位的知识与基于AIML的句子组成模板结合使用,为消费者生成响应句子。最后,通过与关键字匹配机器人进行比较,使用F3和ROUGE指标对提出的机器人进行了评估。评估结果证明了所提机器人的有效性。

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