基于用户满意度的大数据服务可信评价与优化  

Research on Trustworthy Evaluation and Optimization of Big Data Services Based on User Satisfaction Degree

作　　者：张龙昌 白静[3] ZHANG Long-chang;BAI Jing(School of Information Engineering,Suqian University,Suqian 223800,China;Shenzhen Research Institute,Beijing University of Posts and Telecommunications,Shenzhen 518038,China;School of Management Science and Engineering,Dongbei University of Finance and Economics,Dalian 116025,China)

机构地区：[1]宿迁学院信息工程学院,江苏宿迁223800 [2]北京邮电大学深圳研究院,广东深圳518038 [3]东北财经大学管理科学与工程学院,辽宁大连116025

出　　处：《计算机技术与发展》2023年第8期1-8,共8页Computer Technology and Development

基　　金：辽宁省自然科学基金计划项目(2019-ZD-0496);辽宁省教育厅科学研究一般项目(LJKZ1022);宿迁学院人才引进科研启动基金(106-CK4294)。

摘　　要：传统基于QoS的服务评价和优化不能最大化大数据服务的用户满意度,从服务评价和服务运行优化,研究大数据服务用户满意度最大化方法。阐明用户满意度形成机理,研究情景感知的用户满意度模型,解决用户满意度模型不准确问题;揭示评价用户搭便车行为机理,研究评价用户参与评价激励机制,解决用户满意度数据不全面问题;在Logistic回归和社会网络理论的基础上,研究评价用户可信度综合评估方法,解决用户满意度数据不可信问题;探索情景相似的用户Top-K查询和用户满意度数据云模型描述方法,研究基于云模型的可信服务评价方法,解决服务评价不可信问题;阐明服务运行期的服务参与者行为及博弈机理,研究服务运行期的博弈优化方法,解决单方优化方法无法使服务参与者收益最大化问题。为大数据服务的评价和优化提供新的研究思路。The traditional service evaluation and optimization based on QoS cannot maximize the user satisfaction degree of big data service.From the evaluation and the optimization of services,this research studies the method of maximizing user satisfaction degree of big data services.The formation mechanism of user satisfaction degree is expounded and the user satisfaction model based on context awareness is studied to solve the problem of inaccurate user satisfaction model.The mechanism of the evaluation user free riding behaviors is revealed and the incentive mechanism is studied to motivate the evaluation user to solve the problem of user satisfaction degree data is incomplete.On the basis of Logistic regression and social network theory,the comprehensive evaluation method is researched to evaluate the credibility of evaluation user to solve the problem of unreliable user satisfaction degree.The user Top-K query based on scenario similar and user satisfaction data description method of cloud model is explored,and trustworthy service evaluation method is studied to solve the problem of untrustworthy in service evaluation.The behaviors and game mechanism of service participants during the service running period are expounded and the game optimization method of the service running period is studied to solve the problem that the unilateral optimization cannot maximize the income of the service participants.This research provides a new research idea for the evaluation and optimization of big data services.

关 键 词：大数据服务 用户满意度 可信评价与博弈优化 服务质量 服务参与者行为 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]