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中文摘要：
提出了一种基于相对熵的Skyline服务排序方法,根据用户偏好信息定义理想服务,给出一种偏好支配关系,筛选出最符合用户偏好的Skyline服务集,引入相对熵方法来计算理想服务和各个Skyline服务之间的差距,为用户选择出Skyline服务集中Top-k个排序结果.在此基础上提出一种用户偏好度动态修正算法,根据用户对服务的选择计算偏好度调整函数,快速修正用户对不同QoS属性的偏好度.仿真实验与结果表明:本方法能够有效实现有序的Skyline服务集,解决用户对不同属性可能存在的偏好差异,具有更高的用户满意度和良好的扩展性.
英文摘要：
A skyline service ranking algorithm based on KL divergence (KLD-SSRA ) was proposed . A preference dominance relationship was firstly derived from the definition of desired service ,which contributes to filtering skyline services set in accordance with users′preference .Then relative entropy was introduced to calculate the distance between desired service and each skyline service .Top-k sor-ting results in skyline services set were finally selected ,followed with a dynamic correction algorithm of user preference degree (UPD-DCA) .Based on users′choices of services ,UPD-DCA can calculate the preference degree adjustment function and rapidly correct user preference degrees on different QoS attributes .Simulation experiments and results demonstrate that the proposed approaches can achieve an objective of an orderly skyline services set and differentiate potential preference differences on QoS attributes ,which have the performance of a higher user satisfaction and good extensibility .
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