I am pleased to announce today that my collaborators and I have published a new survey paper about episode mining to give an introduction to this nice and interesting subfield of pattern mining. To our knowledge this is the most complete and up-to-date survey paper on this topic.
What is Episode mining? Put simply, it is about analyzing a long sequence of events with timestamps to discover interesting patterns in it such as that some events often appear before other events within some interval of times. This has many applications in real-life such as analyzing relationships between alarms in computer networks.
I have previously written a blog post that gives and introduction to episode mining, and also published a video introduction to episode mining. But this time, it is a survey paper that is more detailed and give a broad and detailed overview of this research topic. You can read the new survey paper here:
Ouarem, O., Nouioua, F., Fournier-Viger, P. (2023). A Survey of Episode Mining. WIREs Data Mining and Knowledge Discovery, Wiley, to appear. |
I hope that you will enjoy this new survey!
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Philippe Fournier-Viger is a distinguished professor working in China and founder of the SPMF open source data mining software.
