Anomaly Mining - Past, Present and Future

Akoglu, Leman

doi:10.24963/ijcai.2021/697

Anomaly Mining - Past, Present and Future

Leman Akoglu

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Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Early Career. Pages 4932-4936.

https://doi.org/10.24963/ijcai.2021/697

Keywords

Data Mining: Anomaly/Outlier Detection
Machine Learning: Deep Learning
Data Mining: Mining Graphs, Semi Structured Data, Complex Data
Machine Learning: Unsupervised Learning

Abstract

Anomaly mining is an important problem that finds numerous applications in various real world do- mains such as environmental monitoring, cybersecurity, finance, healthcare and medicine, to name a few. In this article, I focus on two areas, (1) point-cloud and (2) graph-based anomaly mining. I aim to present a broad view of each area, and discuss classes of main research problems, recent trends and future directions. I conclude with key take-aways and overarching open problems.

Disclaimer. I try to provide an overview of past and recent trends in both areas within 4 pages. Undoubtedly, these are my personal view of the trends, which can be organized differently. For brevity, I omit all technical details and refer to corresponding papers. Again, due to space limit, it is not possible to include all (even most relevant) references, but a few representative examples.

Leman Akoglu. 2021. Anomaly Mining - Past, Present and Future. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21. IJCAI, 4932–4936. https://doi.org/10.24963/ijcai.2021/697

@inproceedings{ijcai2021p697,
  title     = {Anomaly Mining - Past, Present and Future},
  author    = {Akoglu, Leman},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on
               Artificial Intelligence, {IJCAI-21}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Prof. Zhi-Hua Zhou},
  pages     = {4932--4936},
  year      = {2021},
  month     = {8},
  note      = {Early Career},
  doi       = {10.24963/ijcai.2021/697},
  url       = {https://doi.org/10.24963/ijcai.2021/697},
}

TY  - CPAPER
TI  - Anomaly Mining - Past, Present and Future
AU  - Akoglu, Leman
T2  - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2021
SP  - 4932
EP  - 4936
DO  - 10.24963/ijcai.2021/697
UR  - https://doi.org/10.24963/ijcai.2021/697
ER  -