In this blog post, I will share the video of our most recent data mining paper presented last week at ACIIDS 2021. It is about a new algorithm named POERM for about analyzing sequences of events or symbols. The algorithm will find rules called “episode rules” indicating strong relationships between events or symbols. This can be used to understand the data or do prediction. Some applications are for example, to analyse sequence of events in a computer network or analyze the purchase behavior of customers in a store. This paper received the best paper award at ACIIDS 2021!
Here is the link to watch the paper presentation:
https://www.philippe-fournier-viger.com/spmf/videos/poerm_video.mp4
And here is the reference to the paper:
Fournier-Viger, P., Chen, Y., Nouioua, F., Lin, J. C.-W. (2021). Mining Partially-Ordered Episode Rules in an Event Sequence. Proc. of the 13th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2021), Springer LNAI, 12 pages |
The source code and datasets are in the SPMF data mining library.
That is all I wanted to write for today!
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Philippe Fournier-Viger is a full professor working in China and founder of the SPMF open source data mining software.