AD-TIN: Edge Anomaly Detection for Temporal Interaction Networks using Multi-representation Attention
Author:
Affiliation:
1. Kyungpook National University, Daegu, South Korea
Funder
National Research Foundation of Korea
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3625007.3627502
Reference24 articles.
1. Graph neural networks in anomaly detection;Wang S.;Graph Neural Networks: Foundations, Frontiers, and Applications,2022
2. L. Gutiérrez-Gómez A. Bovet and J.-C. Delvenne "Multi-scale anomaly detection on attributed networks " in Proceedings of the AAAI conference on artificial intelligence vol. 34 pp. 678--685 2020.
3. A survey of outlier detection in high dimensional data streams
4. S. Ranshous M. Chaudhary and N. F. Samatova "Efficient outlier detection in hyperedge streams using minhash and locality-sensitive hashing " in Complex Networks & Their Applications VI: Proceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications) pp. 105--116 Springer 2018.
5. Addgraph: Anomaly detection in dynamic graph using attention-based temporal gcn;Zheng L.;IJCAI,2019
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