基于霍克斯过程的社交网络用户关系强度模型

社交网络节点之间的关系强度建模是研究信息传播、实现推荐服务等社交网络服务的关键.传统关系强度模型主要研究简单二元关系与静态关系,未考虑用户交互影响及其动态衰减.本文提出一种基于霍克斯过程的社交网络用户关系强度模型,将用户关系强度视为潜在因子,用户相似性与历史交互行为分别视为潜在因子诱因与表象,并使用霍克斯过程刻画历史交互行为与用户关系强度之间的关系,解决了已有模型未考虑用户历史交互影响及其动态衰减的问题.采用微博社交网络数据对模型进行的评估表明,本模型可以提高用户关系强度预测精度以及基于关系强度排序Top-N邻居节点的覆盖率.

A SociaI Networks User ReIationship Strength ModeI Based on Hawkes Process

The relationship strength model between social network nodes is the key of social networks service such as information dissemination researches and recommendation system.The traditional researches focus on modeling simple bina-ry relations and static relations,without considering dynamic attenuation of user interaction effects.Aiming at this problem, this paper proposes a social networks user relationship strength model based on Hawkes process(HP-URS),which takes the relationship strength,similarity and history interaction behavior between users as a latent factor,latent factor incentive and presentation respectively.This model uses Hawkes process to characterize relationship between history interaction behavior and user relationship strength.This model provides a solution of the disadvantages of the original model without considering user history interaction effects and their attenuation.This paper uses the data from microblog social networks evaluating HP-URS model,and the experimental results show that this model can improve relationship strength prediction accuracy and cov-erage rate of the Top-N neighbor nodes based on relationship strength.