Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications

Haowen Xu, Wenxiao Chen, Nengwen Zhao, Zeyan Li, Jiahao Bu, Zhihan Li, Ying Liu, Youjian Zhao, Dan Pei, Yang Feng, Jie Chen, Zhaogang Wang, Honglin Qiao. Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications. In Pierre-Antoine Champin, Fabien L. Gandon, Mounia Lalmas, Panagiotis G. Ipeirotis, editors, Proceedings of the 2018 World Wide Web Conference on World Wide Web, WWW 2018, Lyon, France, April 23-27, 2018. pages 187-196, ACM, 2018. [doi]

@inproceedings{XuCZLBLLZPFCWQ18,
  title = {Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications},
  author = {Haowen Xu and Wenxiao Chen and Nengwen Zhao and Zeyan Li and Jiahao Bu and Zhihan Li and Ying Liu and Youjian Zhao and Dan Pei and Yang Feng and Jie Chen and Zhaogang Wang and Honglin Qiao},
  year = {2018},
  doi = {10.1145/3178876.3185996},
  url = {http://doi.acm.org/10.1145/3178876.3185996},
  researchr = {https://researchr.org/publication/XuCZLBLLZPFCWQ18},
  cites = {0},
  citedby = {0},
  pages = {187-196},
  booktitle = {Proceedings of the 2018 World Wide Web Conference on World Wide Web, WWW 2018, Lyon, France, April 23-27, 2018},
  editor = {Pierre-Antoine Champin and Fabien L. Gandon and Mounia Lalmas and Panagiotis G. Ipeirotis},
  publisher = {ACM},
}