Anomaly Mining - Past, Present and Future

Author:

Akoglu Leman1

Affiliation:

1. Carnegie Mellon University

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.

Publisher

International Joint Conferences on Artificial Intelligence Organization

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Suspicious: a Resilient Semi-Supervised Framework for Graph Fraud Detection;2023 IEEE 35th International Conference on Tools with Artificial Intelligence (ICTAI);2023-11-06

2. Anomaly Interpretation Method Based on Data Mining for Remote Sensing Satellite Payload;Lecture Notes in Electrical Engineering;2023

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