由于自发地理信息数据主要来源于志愿者上传,不可避免地存在数据质量缺乏保障等问题,故限制了其广泛应用。针对自发地理信息数据质量未知、参考数据难以获取等问题,本文引入了数据可信度的概念,从区域内用户信誉度之和与数据变化趋势2...由于自发地理信息数据主要来源于志愿者上传,不可避免地存在数据质量缺乏保障等问题,故限制了其广泛应用。针对自发地理信息数据质量未知、参考数据难以获取等问题,本文引入了数据可信度的概念,从区域内用户信誉度之和与数据变化趋势2个方面对自发地理信息的可信度进行评价,将定性分析结果进行量化表达。首先,利用李纳斯定理计算区域内用户的信誉度之和获取数据质量的相关信息,以志愿者上传数据中保留的点所占比重作为志愿者的信誉度,构建了基于点统计的志愿者信誉度模型。接着,从数据量变化的趋势中获取数据的质量信息,通过计算研究区域内数据量的变化程度进行数据变化趋势度量。最后,以北京等地区Open Street Map数据作为实验对象,验证了方法的有效性。实验结果表明,利用该方法所得出的实验结果与基于参考数据的质量评价结果总体上保持一致。展开更多
Reputation systems represent soft security mechanisms that complement traditional information security mechanisms. They are now widely used in online e-commerce markets and communities in order to stimulate good behav...Reputation systems represent soft security mechanisms that complement traditional information security mechanisms. They are now widely used in online e-commerce markets and communities in order to stimulate good behaviors as well as to restrain adverse behaviors. This paper analyzes the limitations of the conversational reputation models and proposes an incentive reputation model called the resilient reputation model （RRM） for the distributed reputation systems. The objective of this reputation model is not only to encourage the users to provide good services and, therefore, to maximize the probability of good transaction outcomes, but also to punish those adverse users who are trying to manipulate the application systems. The simulation results indicate that the proposed reputation model （RRM） could effectively resist against the common adverse behaviors, while protecting the profits of sincere users from being blemished by those adversaries.展开更多
文摘由于自发地理信息数据主要来源于志愿者上传,不可避免地存在数据质量缺乏保障等问题,故限制了其广泛应用。针对自发地理信息数据质量未知、参考数据难以获取等问题,本文引入了数据可信度的概念,从区域内用户信誉度之和与数据变化趋势2个方面对自发地理信息的可信度进行评价,将定性分析结果进行量化表达。首先,利用李纳斯定理计算区域内用户的信誉度之和获取数据质量的相关信息,以志愿者上传数据中保留的点所占比重作为志愿者的信誉度,构建了基于点统计的志愿者信誉度模型。接着,从数据量变化的趋势中获取数据的质量信息,通过计算研究区域内数据量的变化程度进行数据变化趋势度量。最后,以北京等地区Open Street Map数据作为实验对象,验证了方法的有效性。实验结果表明,利用该方法所得出的实验结果与基于参考数据的质量评价结果总体上保持一致。
基金the National Basic Research Program of China (973 Program) (Grant No. 2003CB314800)the National Natural Science Foundation of China (Grant No. 60203044)the 242 Program (Grant No. (242)2007A07)
文摘Reputation systems represent soft security mechanisms that complement traditional information security mechanisms. They are now widely used in online e-commerce markets and communities in order to stimulate good behaviors as well as to restrain adverse behaviors. This paper analyzes the limitations of the conversational reputation models and proposes an incentive reputation model called the resilient reputation model （RRM） for the distributed reputation systems. The objective of this reputation model is not only to encourage the users to provide good services and, therefore, to maximize the probability of good transaction outcomes, but also to punish those adverse users who are trying to manipulate the application systems. The simulation results indicate that the proposed reputation model （RRM） could effectively resist against the common adverse behaviors, while protecting the profits of sincere users from being blemished by those adversaries.
