Anomaly Detection in Graph Streams
Papers
- W. Eberle and L. Holder, “Identifying
Anomalies in Graph Streams Using Change Detection,” KDD Workshop on Mining
and Learning in Graphs (MLG), August 2016.
- Y. Yao and L. Holder, “Classification in
Dynamic Streaming Networks,” International Conference on Advances in Social
Network Analysis and Mining (ASONAM), August 2016.
- Y. Yao and L. Holder, “Detecting Concept
Drift in Classification Over Streaming Graphs,” KDD Workshop on Mining and
Learning in Graphs (MLG), August 2016.
- 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.
- Y. Yao and L. Holder, “Scalable
Classification for Large Dynamic Networks,” IEEE International Conference
on Big Data, October 2015.
- W. Eberle and L. Holder, “Scalable
Anomaly Detection in Graphs,” Intelligent Data Analysis, 19(1):57-74, 2015.
- 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)
- 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.
- W. Eberle and L. Holder, “Streaming Data
Analytics for Anomalies in Graphs,” 2015 IEEE International Symposium on
Technologies for Homeland Security, April 2015.
- Y. Yao and L. Holder, “Scalable SVM-based
Classification in Dynamic Graphs,” IEEE International Conference on Data
Mining (ICDM), December 2014.
- S. Akter and L. Holder, “Activity
Recognition using Graphical Features,” International Conference on Machine
Learning and Applications (ICMLA), December 2014.
- 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.
- 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.
- 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.
- J. Narasimhan and L. Holder, “Feature Engineering for Supervised Link
Prediction on Dynamic Social Networks,” International Conference on Data
Mining (DMIN), July 2014.
- 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.
- W. Eberle and L. Holder, “Incremental
Anomaly Detection in Graphs,” IEEE ICDM Workshop on Incremental Clustering,
Concept Drift and Novelty Detection (IcIaNov), December 2013.