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 binary 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 relations

hip 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 coverage rate of the Top-

N

neighbor nodes based on relationship strength.