黄炜, 童青云, 李岳峰. 基于广度学习的异构社交网络敏感实体识别模型研究[J]. 情报学报, 2020, 39(6): 579-588.
Huang Wei, Tong Qingyun, Li Yuefeng. Research on Terror-Related Sensitive Entity Recognition Model of a Heterogeneous Social Network Based on Broad Learning. 情报学报, 2020, 39(6): 579-588.
1 魏建良, 朱庆华. 基于信息级联的网络意见传播及扭曲效应国外研究进展[J]. 情报学报, 2019, 38(10): 1117-1128. 2 陈克寒, 韩盼盼, 吴健. 基于用户聚类的异构社交网络推荐算法[J]. 计算机学报, 2013, 36(2): 349-359. 3 Marrero M, Urbano J, Sánchez-Cuadrado S, et al. Named entity recognition: Fallacies, challenges and opportunities[J]. Computer Standards & Interfaces, 2013, 35(5): 482-489. 4 Webb S, Caverlee, Pu C. Social honeypots: Making friends with a spammer near you[C]// Proceedings of the Fifth Conference on Email and Anti-Spam, Mountain View, 2008: 21-22. 5 Cao Q, Sirivianos M, Yang X Wet al. Aiding the detection of fake accounts in large scale social online services[C]// Proceedings of the 9th USENIX Conference on Networked Systems Design and Implementation. Berkeley: USENIX Association, 2012: 15. 6 Zhao L, Chen F, Dai J, et al. Unsupervised spatial event detection in targeted domains with applications to civil unrest modeling[J]. PLoS ONE, 2014, 9(10): e110206. 7 Yang J. Generalized key player problem[J]. Computational and Mathematical Organization Theory, 2015, 21(1): 24-47. 8 Ding W Y, Zhang Y, Chen C M, et al. Semi-supervised Dirichlet-Hawkes process with applications of topic detection and tracking in Twitter[C]// Proceedings of the International Conference on Big Data. Washington DC: IEEE, 2016. 9 熊建英. 基于可信反馈的微博用户情绪异常预警模型研究[J]. 情报科学, 2017, 35(4): 48-53. 10 谭侃, 高旻, 李文涛, 等. 基于双层采样主动学习的社交网络虚假用户检测方法[J]. 自动化学报, 2017, 43(3): 448-461. 11 朱志国, 张翠, 丁学君, 等. 基于熵权灰色关联模型的重大突发舆情意见领袖识别研究[J]. 情报学报, 2017, 36(7): 66-74. 12 郭博, 许昊迪, 雷水旺. 知乎平台用户影响力分析与关键意见领袖挖掘[J]. 图书情报工作, 2018, 62(20): 122-132. 13 王新栋, 于华, 江成. 社交网络关键节点检测的积极效应问题[J]. 中国科学院大学学报, 2019, 36(3): 425-432. 14 袁丽欣, 顾益军, 赵大鹏. 基于XGBoost方法的社交网络异常用户检测技术[J]. 计算机应用研究, 2020, 37(3): 814-817. 15 Frye P. ISIS cat photo memes attempt to use kittens as propaganda for the islamic state[EB/OL]. [2019-07-16]. http://www.inquisitr.com/1449328/isis-cat-photo-memes-attempt-to-use-kittens-as-propaganda-for-the-islamic-state/. 16 Zhang J W, Yu P S. Broad learning through fusions: An application on social networks[M]. Cham: Springer, 2019. 17 Zhang J W, Yu P S. Broad learning: An emerging area in social network analysis[J]. ACM SIGKDD Explorations Newsletter, 2018, 20(1): 24-50. 18 Zhang J W, Xia C Y, Zhang C W, et al. BL-MNE: Emerging heterogeneous social network embedding through broad learning with aligned autoencoder[C]// Proceedings of the International Conference on Data Mining. IEEE, 2017. 19 Wang F J, Qu Y Z, Zheng L, et al. Deep and broad learning on content-aware POI recommendation[C]// Proceedings of the 3rd International Conference on Collaboration and Internet Computing. IEEE, 2017. 20 Zhang J W, Cui L M, Yu P S, et al. BL-ECD: Broad learning based enterprise community detection via hierarchical structure fusion[C]// Proceedings of the ACM Conference on International and Knowledge Management. New York: ACM Press, 2017: 859-868.
