Anomaly Detection in Graph Streams

Papers

  1. W. Eberle and L. Holder, “Identifying Anomalies in Graph Streams Using Change Detection,” KDD Workshop on Mining and Learning in Graphs (MLG), August 2016.
  2. Y. Yao and L. Holder, “Classification in Dynamic Streaming Networks,” International Conference on Advances in Social Network Analysis and Mining (ASONAM), August 2016.
  3. Y. Yao and L. Holder, “Detecting Concept Drift in Classification Over Streaming Graphs,” KDD Workshop on Mining and Learning in Graphs (MLG), August 2016.
  4. L. Mookiah, W. Eberle and Maitrayi Mondal, “Detecting Change in News Feeds Using a Context-Based Graph,” International Conference on Data Mining (DMIN), July 2016.
  5. Y. Yao and L. Holder, “Scalable Classification for Large Dynamic Networks,” IEEE International Conference on Big Data, October 2015.
  6. W. Eberle and L. Holder, “Scalable Anomaly Detection in Graphs,” Intelligent Data Analysis, 19(1):57-74, 2015.
  7. L. Mookiah, W. Eberle, and L. Holder, “Discovering Suspicious Behavior Using Graph-Based Approach,” International Conference of the Florida AI Research Society (FLAIRS), May 2015. (Nominated for Best Student Paper)
  8. C. Chaparro and W. Eberle, “Detecting Anomalies in Mobile Telecommunication Networks Using a Graph Based Approach,” International Conference of the Florida AI Research Society (FLAIRS), May 2015.
  9. W. Eberle and L. Holder, “Streaming Data Analytics for Anomalies in Graphs,” 2015 IEEE International Symposium on Technologies for Homeland Security, April 2015.
  10. Y. Yao and L. Holder, “Scalable SVM-based Classification in Dynamic Graphs,” IEEE International Conference on Data Mining (ICDM), December 2014.
  11. S. Akter and L. Holder, “Activity Recognition using Graphical Features,” International Conference on Machine Learning and Applications (ICMLA), December 2014.
  12. L. Mookiah, W. Eberle, and L. Holder, “Detecting Suspicious Behavior Using a Graph-Based Approach,” IEEE Symposium on Visual Analytics Science and Technology (VAST), November 2014.
  13. W. Eberle and L. Holder, “A Partitioning Approach to Scaling Anomaly Detection in Graph Streams,” First International Workshop on High Performance Big Graph Data Management, Analysis, and Mining (BigGraphs), IEEE BigData Conference, October 2014.
  14. A. Ray, L. Holder and S. Choudhury, “Frequent Subgraph Discovery in Large Attributed Streaming Graphs,” KDD Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications (BIGMINE), August 2014.
  15. J. Narasimhan and L. Holder, “Feature Engineering for Supervised Link Prediction on Dynamic Social Networks,” International Conference on Data Mining (DMIN), July 2014.
  16. G. Chin, S. Choudhury, J. Feo and L. Holder, “Predicting and Detecting Emerging Cyberattack Patterns Using StreamWorks,” Cyber and Information Security Research Conference (CISRC), April 2014.
  17. W. Eberle and L. Holder, “Incremental Anomaly Detection in Graphs,” IEEE ICDM Workshop on Incremental Clustering, Concept Drift and Novelty Detection (IcIaNov), December 2013.