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| 用户群体满意度最大化的Top-k在线服务评价 |
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赵时海1, 付晓东1,2, 岳昆3, 刘骊1, 冯勇1, 刘利军1
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1.昆明理工大学 信息工程与自动化学院, 云南 昆明 650504;2.云南省计算机应用技术重点实验室(昆明理工大学), 云南 昆明 650504;3.云南大学信息学院, 云南 昆明 650504
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| 摘要: |
| 考虑用户评价准则不一致的在线服务评价通常以服务的完整排序作为评价结果，而不是选择出使用户群体满意度最大的Top-k在线服务集合，使评价结果难以满足Top-k在线服务评价场景的合理性和公平性需求.为此，提出了一种用户群体满意度最大化的Top-k在线服务评价方法.该方法首先定义用户群体满意度指标，以衡量选择的k个在线服务的合理性；其次，考虑用户评价准则不一致及用户偏好信息不完整的情况，采用Borda规则将用户对在线服务的偏好关系构造为用户-服务满意度矩阵；然后借鉴Monroe比例代表思想，将Top-k在线服务评价问题建模为寻找最大化用户群体满意度的在线服务集合的优化问题；最后采用贪心算法对该优化问题进行求解，将得到的在线服务集合作为Top-k评价结果.通过理论分析和实验验证了该方法的合理性和有效性.理论分析表明，该方法满足Top-k在线服务评价所需的比例代表性和公平性.同时，实验结果也表明，该方法能够在合理的时间内获得接近用户群体满意度理想上界的评价结果，可以有效地辅助用户群体做出正确的服务选择决策.另外，该方法还可以在用户偏好不完整的情况下实现Top-k在线服务评价. |
| 关键词: 在线服务 Top-k在线服务评价 用户偏好 Monroe规则 贪心算法 |
| DOI：10.13328/j.cnki.jos.006089 |
| 分类号:TP311 |
| 基金项目:国家自然科学基金（61962030，61862036，61860318）；NSFC-云南联合基金（U1802271）；云南省基础研究计划（2019FJ011）；云南省中青年学术和技术带头人后备人才培养计划（202005AC160036） |
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| Top-k Online Service Evaluating to Maximize Satisfaction of User Group |
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ZHAO Shi-Hai1, FU Xiao-Dong1,2, YUE Kun3, LIU Li1, FENG Yong1, LIU Li-Jun1
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1.Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650504, China;2.Yunnan Key Laboratory of Computer Technology Application (Kunming University of Science and Technology), Kunming 650504, China;3.School of Information Science and Engineering, Yunnan University, Kunming 650504, China
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| Abstract: |
| Online service evaluations that consider inconsistent user evaluation criteria usually use a complete ranking of services as the evaluation result, instead of selecting the Top-k online service set that maximizes the satisfaction of the user group. Thus, it makes the evaluation results cannot satisfy the rationality and fairness requirement in the scenario of Top-k online service evaluation. This study proposes a Top-k online service evaluation method that maximizes the satisfaction of user group. Firstly, a metric of user group satisfaction is defined to measure the rationality of the selected k online services. Secondly, considering the inconsistency of user evaluation criteria and incomplete user preference information, the Borda rule is used to construct user-service matrix based on users' preference relationship for online services. Then, inspired by the theory of Monroe proportional representation, the Top-k online service evaluation problem is modeled as an optimization problem to find a set of online services that maximizes satisfaction of the user group. Finally, a greedy algorithm is designed to solve the optimization problem and the obtained set of online services is served as the result of Top-k services evaluation. The rationality and effectiveness of the method are verified by theoretical analysis and experiments study. Theoretical analysis shows that the proposed method satisfies the proportional representation and fairness required for Top-k online service evaluation. Meanwhile, experiments also show that the method can obtain the result close to the ideal upper bound of the user group satisfaction in the reasonable time, so that the user group can make right service choice decision. In addition, the method can also realize Top-k online service evaluation when users' preferences are incomplete. |
| Key words: online service Top-k online service evaluation user preference Monroe rule greedy algorithm |
