在当前服务计算背景下,针对用户难以获得满足需求的可信服务问题,提出基于社会网络动态反馈的Web服务信任度模型.基于用户使用经验设计服务直接信任度算法,对服务交易情况进行动态跟踪和监测.当用户缺乏使用某服务的直接经验时,基于社会网络中服务使用者信任度,聚合其他服务使用者对服务的直接信任度,计算该服务的间接信任度.采用修正因子进行修正,以提高社会网络节点及关联服务可信性.算法分析表明,该方法是可行和有效的.
In the current service computing background, it is difficult for users to obtain the trusted services. Aiming at this problem, a Web services trust model based on social network dynamic feedback is proposed. An algorithm for computing direct trust value of the service is designed by using individual user's experience. The transactions of the services are dynamically tracked and monitored by the proposed algorithm. When a user has no direct experience of a service, based on the users" trust values in the social network the indirect trust value of the service can be calculated by gathering a number of other user's direct trust values of the service. As the social network nodes may recommend untrue services, the correction factor is used to amend the trust of social network peers. The analysis of the proposed algorithms shows that this method is feasible and effective.