CmaGraph: A TriBlocks Anomaly Detection Method in Dynamic Graph Using Evolutionary Community Representation Learning

Weiqin Lin, Xianyu Bao, Mark Junjie Li. CmaGraph: A TriBlocks Anomaly Detection Method in Dynamic Graph Using Evolutionary Community Representation Learning. In Igor Farkas, Paolo Masulli, Sebastian Otte, Stefan Wermter, editors, Artificial Neural Networks and Machine Learning - ICANN 2021 - 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 14-17, 2021, Proceedings, Part I. Volume 12891 of Lecture Notes in Computer Science, pages 105-116, Springer, 2021. [doi]

@inproceedings{LinBL21-0,
  title = {CmaGraph: A TriBlocks Anomaly Detection Method in Dynamic Graph Using Evolutionary Community Representation Learning},
  author = {Weiqin Lin and Xianyu Bao and Mark Junjie Li},
  year = {2021},
  doi = {10.1007/978-3-030-86362-3_9},
  url = {https://doi.org/10.1007/978-3-030-86362-3_9},
  researchr = {https://researchr.org/publication/LinBL21-0},
  cites = {0},
  citedby = {0},
  pages = {105-116},
  booktitle = {Artificial Neural Networks and Machine Learning - ICANN 2021 - 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 14-17, 2021, Proceedings, Part I},
  editor = {Igor Farkas and Paolo Masulli and Sebastian Otte and Stefan Wermter},
  volume = {12891},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-030-86362-3},
}