Anomaly Mining - Past, Present and Future
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.
Cite
Text
Akoglu. "Anomaly Mining - Past, Present and Future." International Joint Conference on Artificial Intelligence, 2021. doi:10.24963/IJCAI.2021/697Markdown
[Akoglu. "Anomaly Mining - Past, Present and Future." International Joint Conference on Artificial Intelligence, 2021.](https://mlanthology.org/ijcai/2021/akoglu2021ijcai-anomaly/) doi:10.24963/IJCAI.2021/697BibTeX
@inproceedings{akoglu2021ijcai-anomaly,
title = {{Anomaly Mining - Past, Present and Future}},
author = {Akoglu, Leman},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2021},
pages = {4932-4936},
doi = {10.24963/IJCAI.2021/697},
url = {https://mlanthology.org/ijcai/2021/akoglu2021ijcai-anomaly/}
}