Addressing the class imbalance problem in Twitter spam detection using ensemble learning
暂无分享,去创建一个
Jun Zhang | Yu Wang | Chao Chen | Shigang Liu | Yang Xiang | Yang Wang | Chao Chen | Jun Zhang | Yang Xiang | Shigang Liu
[1] Danah Boyd,et al. Detecting Spam in a Twitter Network , 2009, First Monday.
[2] Kyumin Lee,et al. Uncovering social spammers: social honeypots + machine learning , 2010, SIGIR.
[3] Guofei Gu,et al. Analyzing spammers' social networks for fun and profit: a case study of cyber criminal ecosystem on twitter , 2012, WWW.
[4] Alok N. Choudhary,et al. Towards Online Spam Filtering in Social Networks , 2012, NDSS.
[5] Hosung Park,et al. What is Twitter, a social network or a news media? , 2010, WWW '10.
[6] Xianchao Zhang,et al. Detecting Spam and Promoting Campaigns in the Twitter Social Network , 2012, 2012 IEEE 12th International Conference on Data Mining.
[7] Chao Yang,et al. Empirical Evaluation and New Design for Fighting Evolving Twitter Spammers , 2013, IEEE Trans. Inf. Forensics Secur..
[8] Wei-Pang Yang,et al. An intelligent three-phase spam filtering method based on decision tree data mining , 2016, Secur. Commun. Networks.
[9] R. Polikar,et al. Ensemble based systems in decision making , 2006, IEEE Circuits and Systems Magazine.
[10] Daniel Dajun Zeng,et al. Filtering spam in Weibo using ensemble imbalanced classification and knowledge expansion , 2015, 2015 IEEE International Conference on Intelligence and Security Informatics (ISI).
[11] Alex Hai Wang,et al. Don't follow me: Spam detection in Twitter , 2010, 2010 International Conference on Security and Cryptography (SECRYPT).
[12] Rishabh Kaushal,et al. Rumor detection in twitter: An analysis in retrospect , 2015, 2015 IEEE International Conference on Advanced Networks and Telecommuncations Systems (ANTS).
[13] Xiao Chen,et al. 6 million spam tweets: A large ground truth for timely Twitter spam detection , 2015, 2015 IEEE International Conference on Communications (ICC).
[14] Dawn Xiaodong Song,et al. Suspended accounts in retrospect: an analysis of twitter spam , 2011, IMC '11.
[15] Haibo He,et al. Learning from Imbalanced Data , 2009, IEEE Transactions on Knowledge and Data Engineering.
[16] Robert Sabourin,et al. Adaptive ROC-based ensembles of HMMs applied to anomaly detection , 2012, Pattern Recognit..
[17] Jun Zhang,et al. Fuzzy-Based Feature and Instance Recovery , 2016, ACIIDS.
[18] Yu Wang,et al. An Ensemble Learning Approach for Addressing the Class Imbalance Problem in Twitter Spam Detection , 2016, ACISP.
[19] Christopher Ke,et al. AN IN-DEPTH ANALYSIS OF ABUSE ON TWITTER , 2014 .
[20] Gianluca Stringhini,et al. Detecting spammers on social networks , 2010, ACSAC '10.
[21] Yang Gao,et al. Term Space Partition Based Ensemble Feature Construction for Spam Detection , 2016, DMBD.
[22] Ali Dehghantanha,et al. Investigating Social Networking applications on smartphones detecting Facebook, Twitter, LinkedIn and Google+ artefacts on Android and iOS platforms , 2016 .
[23] Dawn Xiaodong Song,et al. Design and Evaluation of a Real-Time URL Spam Filtering Service , 2011, 2011 IEEE Symposium on Security and Privacy.
[24] Kim-Kwang Raymond Choo,et al. Cloud Storage Forensics , 2013, Contemporary Digital Forensic Investigations of Cloud and Mobile Applications.
[25] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[26] Jong Kim,et al. WarningBird: A Near Real-Time Detection System for Suspicious URLs in Twitter Stream , 2013, IEEE Transactions on Dependable and Secure Computing.
[27] Ludmila I. Kuncheva,et al. Classifier Ensembles for Changing Environments , 2004, Multiple Classifier Systems.
[28] Jong Kim,et al. Spam Filtering in Twitter Using Sender-Receiver Relationship , 2011, RAID.
[29] Kim-Kwang Raymond Choo,et al. The cyber threat landscape: Challenges and future research directions , 2011, Comput. Secur..