基于动态贝叶斯网络的社交圈归属匹配模型

为了帮助社交网中新成员寻找与之最为合适的社交圈，尝试采用动态贝叶斯网（DBN）理论解决社交网分析应用中成员（节点）与社交圈（集合）的匹配问题。将圈内成员个人的多项兴趣爱好程度作为描述社交圈基本属性的特征向量，对每一类圈子建立了带有辅助信息形式的DBN模型，求解最大输出概率即为最佳匹配对象。结果表明，在客观测试和主观评价两方面，该模型都收到了较为满意的结果。

Social network matching model using dynamic Bayesian network

In order to help a new client in the social network finding the best matching circle of social communication for itself, the Dynamic Bayesian Network (DBN) theory was introduced. The group set up by several hobbies' degrees was described as the eigenvector of the circle's property and DBNs with auxiliary information were set up for each circle using this eigenvector. The best matching result is the DBNs maximal output. Objective and subjective experiments show that this model can achieve satisfactory result for the matching task.