基于用户感知的移动智能终端用户行为获取与仿真预测框架的设计与实现

Chunji Hao, Yi Zhou
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引用次数: 2

摘要

目前,移动智能终端各种应用的流程安排只是一个从开发者到用户的单向过程,大部分都是在一定范围内仅凭产品设计师的经验或市场调研进行安排。实时性、便携性和定位性是移动终端区别于传统互联网的特点。相关信息需要快速提供给用户,让用户快速做出消费决策。如何有效获取语境信息,基于语境预测用户的消费行为,成为个性化服务领域面临的课题。本文分析了大数据多数据源关联的综合质量,分析了基于用户感知的用户行为获取与仿真预测框架构建方法。从而最大程度地满足用户的需求,减少用户的操作,实现用户体验的个性化。未来优化需要结合高流量、高用户量、高投诉量等进行多数据源关联分析,旨在提升用户感知。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and Implementation of User Behavior Acquisition and Simulation Prediction Framework for Mobile Intelligent Terminal Based on User Perception
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.
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