Journal of Computer Applications ›› 2017, Vol. 37 ›› Issue (7): 1983-1988.DOI: 10.11772/j.issn.1001-9081.2017.07.1983

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Online service evaluation based on social choice theory

LI Wei1, FU Xiaodong1,2, LIU Li1, LIU Lijun1   

  1. 1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming Yunnan 650500, China;
    2. Aviation College, Kunming University of Science and Technology, Kunming Yunnan 650500, China
  • Received:2016-12-16 Revised:2017-03-05 Online:2017-07-10 Published:2017-07-18
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61462056, 71161015, 81560296), the Applied Fundamental Research Project of Yunnan Province (2014FA028, 2014FB133).


李威1, 付晓东1,2, 刘骊1, 刘利军1   

  1. 1. 昆明理工大学 信息工程与自动化学院, 昆明 650500;
    2. 昆明理工大学 航空学院, 昆明 650500
  • 通讯作者: 付晓东
  • 作者简介:李威(1990-),男,湖北荆州人,硕士研究生,主要研究方向:服务计算、智能决策;付晓东(1975-),男,云南镇雄人,教授,博士,CCF高级会员,主要研究方向:服务计算、决策理论与方法、软件工程;刘骊(1979-),女,重庆人,副教授,博士,主要研究方向:服务计算、智能家居;刘利军(1978-),男,河南辉县人,讲师,硕士,主要研究方向:服务计算、医疗信息系统。
  • 基金资助:

Abstract: The inconformity of user evaluation standard and preference results in unfair comparability between online services in cyberspace, thereby the users are hardly to choose satisfactory online services. The ranking method to calculate the online service quality based on social choice theory was proposed. First, group preference matrix was built according to the user-service evaluation matrix given by users; second, 0-1 integer programming model was built based on group preference matrix and Kemeny social choice function; at last, the optimal service ranking results could be obtained by solving this model. The individual preferences were aggregated to group preference in the proposed method; the decision was consistent with the majority preference of the group and maximum consistency with the individual preference. The proposed method's rationality and effectiveness were verified by theoretical analysis and experiment results. The experimental results show that the proposed method can solve the incomparability between online services, realize the online service quality ranking, effectively resisted the recommendation attacks. So it has strong anti-manipulation.

Key words: online service, social choice theory, Kemeny function, service ranking, group decision

摘要: 用户评价标准不一致和偏好不一致导致网络空间中的在线服务之间不具备公正的可比较性,从而用户难以选择到满意的在线服务,因此,提出了基于社会选择理论计算在线服务优劣的排序方法。首先,根据用户给出的用户-服务评价矩阵构建群体偏好矩阵;然后,基于群体偏好矩阵和Kemeny社会选择函数构建0-1整数规划模型;最后,通过求解该模型可得到服务的最优排序结果。该方法聚合个体偏好为群体偏好,决策符合群体大多数人的偏好且与个体偏好保持最大的一致性。通过理论分析和实验验证了该方法的合理性和有效性。实验结果表明,该方法能有效地解决在线服务之间的不可比较性问题,实现在线服务的优劣排序,并可以有效抵制推荐攻击,具有较强的抗操纵性。

关键词: 在线服务, 社会选择理论, Kemeny函数, 服务排序, 群体决策

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