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Data mining of customer choice behavior in internet of things within relationship network

机译:关系网络中物联网中客户选择行为的数据挖掘

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摘要

Internet of Things has changed the relationship between traditional customer networks, and traditional information dissemination has been affected. Smart environment accelerates the changes in customer behaviors. Apparently, the new customer relationship network, benefitted from the Internet of Things technology, will imperceptibly influence customer choice behaviors for the cyber intelligence. In this work, we selected 298 customers' click browsing records as training data, and collected 50 customers who used the platform for the first time as research objects. and use the smart customer relationship network correspond to cyber intelligence to build the customer intelligence decision model in Internet of Things. The results showed that the MAE (Mean Absolute Deviation) of the customer trust evaluation model constructed in this study is 0.215, 45% improvement over the traditional equal assignment method. In addition, customer's consumer experience can be enhanced with the support of data mining technology in cyber intelligence. Our work indicated the key to build eliminates confusion in customer choice behavior mechanism is to establish a consumer-centric, effective network of customers and service providers, and to be supported by the Internet of Things, big data analysis, and relational fusion technologies.
机译:物联网改变了传统客户网络之间的关系,传统信息传播受到了影响。智能环境加快了客户行为的变化。显然,受益于物联网技术的新客户关系网络将对网络智能的客户选择行为产生不可感知的影响。在这项工作中,我们选择了298个客户的点击浏览记录作为培训数据,并收集了50个首次使用该平台的客户作为研究对象。并使用与网络智能相对应的智能客户关系网络来构建物联网中的客户智能决策模型。结果表明,本研究构建的客户信任评估模型的MAE(平均绝对偏差)为0.215,比传统的均等分配方法提高了45%。此外,借助网络智能中的数据挖掘技术,可以增强客户的消费者体验。我们的工作表明,建立消除客户选择行为机制混乱的关键是建立以消费者为中心的有效客户和服务提供商网络,并得到物联网,大数据分析和关系融合技术的支持。

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