《山东大学学报(理学版)》 ›› 2019, Vol. 54 ›› Issue (3): 10-17, 27.doi: 10.6040/j.issn.1671-9352.2.2018.084
谢小杰1,2(
),梁英1,*(),董祥祥1,2
Xiao-jie XIE1,2(),Ying LIANG1,*(),Xiang-xiang DONG1,2
摘要：
分析识别社交网络用户敏感信息，有利于从技术上量化隐私泄露程度，进行隐私保护。针对现有的用户属性识别方法需要对用户属性取值进行强假设的问题，结合RL迭代分类框架和扩展wvRN关系识别的方法，提出了一种社交网络用户敏感属性迭代识别方法。通过卷积神经网络提取用户文本特征进行识别，结合邻居结点迭代地进行关系识别，不仅弱化了对用户属性的假设，而且提高了可用性。实验结果表明，通过在社交网络中获取少量的标注数据，对迭代识别方法设置合理的参数值，可以获得较好的用户敏感属性识别结果。
中图分类号:
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