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A Social Network Approach To Resolving Group-level Conflict In Context-aware Services

机译:解决上下文感知服务中组级别冲突的社交网络方法

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Group conflict that occurs when delivering context-aware services negatively affects service usage within a specific service space, and researchers have proposed few conflict resolution methods to address the issue. This paper presents a methodology to autonomously resolve the conflict arising between users in identical contexts, such as place and computing resources. To do so, a two-phase case-based reasoning method is proposed. To minimize privacy concerns, a social network model is applied to produce key social context data, secondary to personal data, and which is used in place of the users' personal data for case-based reasoning. To show the feasibility of the idea proposed in this paper, a prototype system with simulation-based validation is tested to determine conflict resolution strategies and a simulation test has been performed.
机译:提供上下文感知服务时发生的组冲突会对特定服务空间内的服务使用产生负面影响,研究人员提出了几种解决冲突的方法来解决该问题。本文提出了一种方法,可以自动解决在相同环境(例如位置和计算资源)中用户之间产生的冲突。为此,提出了一种基于案例的两阶段推理方法。为了最大程度地减少对隐私的关注,将社交网络模型应用于生成次要的个人社交环境数据,并将其替换为用户的个人数据以进行基于案例的推理,这些数据是个人数据的第二位。为了证明本文提出的想法的可行性,测试了基于仿真的原型系统以确定冲突解决策略,并进行了仿真测试。

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