摘要
针对现实生活中人们的社交关系和兴趣爱好对节点进行社会活动的驱动作用,提出了一种基于用户兴趣相似性的节点移动模型。该模型将节点对活动的感兴趣程度抽象为一个兴趣概率矩阵,利用皮尔逊相关系数计算节点的兴趣相似群体。仿真实验表明,该模型在一定时间范围内节点的相遇时间间隔和相遇持续时间的互补累积分布函数近似服从幂律分布,更加接近真实数据集统计结果得到的曲线,同时也表明了节点在进行夜间活动时,具有很强的时空规律性。
According to the driving effect of people＇s social relations and interests on the social activities of nodes, a mobility model based on user interest similarity was presented. The interest degree of node to the activities was described with a interest probability matrix, and Pearson correlation coefficient was used to calculate the similar interest groups of nodes. Simulation results show that, the complementary cumulative density function of inter-contact time and contact duration in a certain time approximately follows power-law distribution, which is more consistent with the curve obtained from statistical results of real data set. Additionally, strong space-time regularity is observed when nodes are involved in the activities in the evening.
出处
《计算机应用》
CSCD
北大核心
2015年第9期2457-2460,共4页
journal of Computer Applications
关键词
社交关系
兴趣
皮尔逊相关系数
移动模型
social relation
interest
pearson correlation coefficient
mobility model
