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Design and Implementation of User Behavior Acquisition and Simulation Prediction Framework for Mobile Intelligent Terminal Based on User Perception

机译:基于用户感知的移动智能终端用户行为采集与仿真预测框架的设计与实现

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At present, the flow arrangement of various applications of mobile intelligent terminals is only a one-way process from developers to users, and most of them are arranged only by the experience of product designers or market research within a certain range. Real-time, portability and positioning are the characteristics of mobile terminals that are different from traditional Internet. Relevant information needs to be given to users quickly, so that users can make consumption decisions quickly. How to obtain context information effectively and predict users' consumption behavior based on context has become a topic facing personalized service field. This paper analyzes the comprehensive quality of the large data multi data source Association, and analyzes the user behavior acquisition and simulation prediction framework construction method based on user perception. Thus, it can meet the needs of users to the maximum extent, reduce the operation of users and realize the personalization of user experience. In the future, the optimization needs to combine high traffic, high user volume, high complaints and so on to carry out multi data source correlation analysis, aiming at improving user perception.
机译:目前,移动智能终端的各种应用的流量布置仅是从开发人员到用户的单向过程,而且大多数只能通过在一定范围内的产品设计师或市场研究的经验安排。实时,可移植性和定位是与传统互联网不同的移动终端的特征。需要快速向用户提供相关信息,以便用户可以快速制作消费决策。如何有效地获取上下文信息并基于上下文预测用户的消费行为已成为面临个性化服务字段的主题。本文分析了大数据多数据源关联的全面质量,并分析了基于用户感知的用户行为采集和仿真预测框架施工方法。因此,它可以满足用户需求到最大程度,减少用户的操作并实现用户体验的个性化。在未来,优化需要将高流量,高用户卷,高投诉等结合开展多数据源相关性分析,旨在提高用户感知。

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