Anomaly Detection in Microblogging via Co-Clustering

@article{Yang2015AnomalyDI,
  title={Anomaly Detection in Microblogging via Co-Clustering},
  author={Wu Yang and Guowei Shen and Zhongyong Wang and Liangyi Gong and Miao Yu and Guozhong Dong},
  journal={Journal of Computer Science and Technology},
  year={2015},
  volume={30},
  pages={1097-1108}
}
Traditional anomaly detection on microblogging mostly focuses on individual anomalous users or messages. Since anomalous users employ advanced intelligent means, the anomaly detection is greatly poor in performance. In this paper, we propose an innovative framework of anomaly detection based on bipartite graph and co-clustering. A bipartite graph between users and messages is built to model the homogeneous and heterogeneous interactions. The proposed co-clustering algorithm based on nonnegative… CONTINUE READING

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