Research on Relationship Strength under Personalized Recommendation Service

Abstract

Relationship of users in an online social network can be applied to promote personalized recommendation services. The measurement of relationship strength between user pairs is crucial to analyze the user relationship, which has been developed by many methods. An issue that has not been fully addressed is that the interaction behavior of individuals subjected to the activity field preference and interactive habits will affect interactive behavior. In this paper, the three-way representation of the activity field is given firstly, the contribution weight of the activity filed preferences is measured based on the interactions in the positive and boundary regions. Then, the interaction strength is calculated, integrating the contribution weight of the activity field preference and interactive habit. Finally, user relationship strength is calculated by fusing the interaction strength, common friend rate and similarity of feature attribute. The experimental results show that the proposed method can effectively improve the accuracy of relationship strength calculation.