节点文献
社交网络中网络空间安全用户挖掘模型研究
Automatically Extract Cybersecurity User from Social Network
【摘要】 当下如何从社交网络平台中自动准确地挖掘网络空间安全相关用户具有重要意义。在现有的基于社交关系的相似度算法基础上,结合基于动态交互信息的相似度算法,加权综合两种用户相似度算法,提出一种新的用户相似度算法,从而初步计算社交网络中网络空间安全相似用户。再通过基于机器学习的用户分类算法,从网络空间安全相似用户中进一步准确地检测网络空间安全领域的用户,最终构建社交网络的网络空间安全用户挖掘模型。
【Abstract】 It is important to automatically and accurately to excavate cyber security users from social networking platforms. First,in order to gain the similarity cybersecurity users from social network approximately,constructs a new user similarity calculation model based on users’ social relations and dynamic interaction information through presenting a comprehensive similarity measurement method by weighting. Then uses user classification methods based on machine learning algorithms to detect the cybersecurity users more accurately from the previous similar users,and finally constructs the cybersecurity users extracting model.
【Key words】 Social Network; Dynamic Interaction Information; User Classification; Cybersecurity; User Extracting Model;
- 【文献出处】 现代计算机 ,Modern Computer , 编辑部邮箱 ,2020年12期
- 【分类号】TP393.08
- 【被引频次】2
- 【下载频次】97