基于社会选择和社会影响的社交网络社群分类与群推荐策略研究

Community Classification and Group Recommendation Strategy of Online Social Networks Based on Social Selection and Social Influence

社会选择和社会影响是在线社交网络社群形成的两个主要因素,如果能有效对网络社群中用户和群体进行分类,就可以采取不同的群推荐策略,实现群体满意最大化。利用偏好对表示群用户偏好,利用矩阵分解和贝叶斯个性化排序方法,考查社会选择和影响对用户偏好的影响程度,实现群用户和群体的分类,进而提出2种群推荐策略。最后通过2个数据集的实验验证,表明本文提出的基于用户和群体分类的群推荐策略是有效的。

Social selection and social influence are the two main factors in the formation of online social network community. If classification of users and groups in network community effectively,it can take different strategies for group recommendation,so can realize the community satisfaction maximization. The paper used pairwise to express user preference preference,used matrix factorization and Bayesian personalized ranking method to judge social selection and influence on user preferences. And it realized the classification of users and groups,Then proposed 2 group recommendation strategies. Finally,the experimental results of 2 datasets showed that the proposed group recommendation strategy based on classification of users and groups is effective.