In this blog post, I will talk about the IEEE DSAA 2022 conference, which was held from the 13th to the 16th October 2022.
What is IEEE DSAA?
DSAA 2022 is the 9th edition of the IEEE International Conference on Data Science and Advanced Analytics (DSAA). DSAA is an international conference that has been held in many countries, and focuses on data mining, data science, big data, machine learning and relatedtopics.
DSAA is a relatively young conference compared to some top data mining and machine learning conferences, but DSAA has become more and more successful over the years.
This year, the DSAA conference was planned to be held in the city of Shenzhen, China. But due to the COVID-19 pandemic, the conference was held in online mode (local organization by Shenzhen University), and using Zoom as online videoconferencing platform.
Proceedings of DSAA 2022
The proceedings of DSAA are published by IEEE.
Authors could submit a paper to the main track of DSAA. But besides that, the DSAA conference hosts several special sessions on emerging topics. It is interesting for authors that papers accepted in the special sessions are published as regular papers in the proceedings of DSAA. This year, I have been co-organizer of a special session called DSSBA (1st Special Session on Data Science for Social and Behavioral Analytics), that has been quite successful with 5 papers accepted (more on that later).
Another interesting aspect about DSAA is that there are two special issues, respectively organized in the International Journal on Data Science and Analytics (JDSA) journal and the Machine Learning Journal (MLJ). Authors could submit papers to these special issues and then present the articles at the conference.
Keynote speaker from the main conference
This year, there was a good line up of keynote speakers:
The conference opening was on the 13th October. Several interesting information were given about the DSAA conference. Here are some slides from the opening:
Country distribution for application track:
Country distribution for the research track:
The paper acceptance rate statistics:
The main topics of papers published in DSAA:
Some awards were given with some of them receiving a cash prize of 1000$ USD.
The DSSBA special session
At DSAA 2022, I co-organized a special session called DSSBA 2022 (1st Special session on Data Science for Social and Behavioral Analytics). This special session received many papers, among which 5 have been accepted for publications as regular papers in the conference.
A keynote talk was given in this special session by Prof. Yun Sing Koh from the University of Auckland, New Zealand. She presented some of her latest research work related to machine learning to tackle environmental science challenges. In particular, she presented two recent research projects published in the Machine Learning journal and in AAAI 2022, which are about air quality index inference and about algal bloom monitoring, respectively. Below, I share a few slides from her talk:
For more details about these two research projects, you can see these two papers:
- Olivier Graffeuille, Yun Sing Koh, Jörg Wicker, Moritz K. Lehmann: Semi-supervised Conditional Density Estimation with Wasserstein Laplacian Regularisation. AAAI 2022: 6746-6754
- Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet, Gustavo Olivares, Guy Coulson: Analyzing and repairing concept drift adaptation in data stream classification. Mach. Learn. 111(10): 3489-3523 (2022)
In the DSSBA special session, we also had five paper presentations, where the last three papers are about pattern mining.
- SA-FGDEM: A Self-adaptive E-Learning Performance Prediction Model
Wang, Liping; Ye, Mingtao; Zhang, Guodao; Sheng, Xin; Zhang, Jingran
- Heterogeneous Drift Learning: Classification of Mix-Attribute Data with Concept Drifts
Zhao, Lang; Zhang, Yiqun; Ji, Yuzhu; Zeng, An; Gu, Fangqing; Luo, Xiaopeng
- Fast Mining RFM Patterns for Behavioral Analytics
Wan, Shicheng; Deng, Jieyin; Chen, Jiahui; Gan, Wensheng; Yu, Philip S
- Constraint-based Sequential Rule Mining
Yin, Zhaowen; Gan, Wensheng; Huang, Gengsen ; Wu, Yongdong; Fournier-Viger, Philippe Discovering Geo-referenced
- Periodic-Frequent Patterns in Geo-referenced Time Series Databases Ravikumar,
Penugonda; Palla, Likhitha; T, Chandrasekhar; RAGE, Uday Kiran; Watanobe, Yukata; Zettsu, Koji
Other paper presentations
There was also several interesting paper presentations at the conference and talks but due to my busy schedule, I was not able to attend many of them. An interesting paper that I saw related to periodic pattern mining is:
Discovering Periodicity in Locally Repeating Patterns
Alfred Krzywicki (University of Adelaide); Ashesh Mahidadia (Rich Data Corporation); Michael Bain (University of New South Wales)
Overall, the conference has been very interesting and well-organized. I will try to participate again to IEEE DSAA, next year.
Philippe Fournier-Viger is a distinguished professor of computer science