Page 76 - 《软件学报》2021年第11期

3402 Journal of Software 软件学报 Vol.32, No.11, November 2021

在线服务评价方法.该方法考虑了用户评价准则不一致的问题,首先将用户群体满意度作为指标以衡量在线服
务能否被选择,然后将 Top-k 在线服务评价问题转化为基于 Monroe 规则的分配最优化问题,再采用贪心算法寻
找最大化群体满意度的 k 个服务作为的 Top-k 在线服务评价结果.通过理论分析和实验验证,表明了该方法的合
理性、有效性及高效性.另外,方法在用户提供完整的偏好排序或用户只提交完整排序比例仅为 10%的 Top-t 服
务这两种情况下,均可得到较高的用户群体满意度.
未来工作中,将探索评价模型的增量更新算法,以在上一次评价结果的基础上,结合新的信息变化,快速获
取评价结果.同时,还将对模型的抗操纵性进行分析,并提出针对性的抗操纵方法.

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