机构地区: 吉首大学信息管理与工程学院
出 处: 《计算机应用研究》 2011年第8期3004-3006,3017,共4页
摘 要: 网络技术的发展产生了大量的网络用户,他们之间潜藏的社会关系越来越多地引起了人们的注意,大量的社交网络发现算法已被提出。但是,以前的研究多建立在关系数据可直接获取的基础之上。实际上,网络数据多以用户个体行为形式存在,数据实时变化。基于用户使用网络的行为日志分析,提出基于时空数据分析模型的社会关系发现算法,算法主要包括实际分析和关系发现两个步骤。通过实验表明,本算法能很好地发现用户行为中潜藏的社会关系。 With the development and application of network technology,comes a greater amount of data about users.The underlying social relationship between the users more and more attracted people's attention,and a lot of social network discovery algorithm has been proposed.However,many previous studies suppose that the relation data could be achieved directly.However,the social information is hard to be found according to the network data because it's aim to the user's individual behavior.Based on the users' behavior analysis,this paper proposed a temporal and spatial data analysis model,and designed the social relationship discovery algorithm.The algorithm included two steps-getting events and finding relationship.Experiment shows that the algorithm could find the underlying user's relationship effective.
领 域: [自动化与计算机技术] [自动化与计算机技术]