In this blog post, I will talk about the DEXA 2021 and DAWAK 2021 conferences that I have attended, September 27–30, 2021. Those two conferences are co-located and co-organized every year in different countries of Europe. This year, these conferences were held virtually due to the COVID pandemic.
What is DEXA and DAWAK?
DEXA 2021 is the 32nd International Conference on Database and Expert Systems Applications. It is a conference oriented towards database technology and expert systems, but that also accepts data mining papers.
DAWAK 2021 is the 23rd International Conference on Big Data Analytics and Knowledge Discovery. The focus is similar to DEXA but more oriented towards data mining and machine learning. Several years ago, the DAWAK conference was named “Data Warehousing and Knowledge Discovery, hence DAWAK). But the name has changed in recent years.
The proceedings of DEXA and DAWAK are both published by Springer in the LNAI series, which ensures good visibility and indexing in EI, DBLP and other popular publication databases. The DEXA conference is older and viewed as a better conference than DAWAK by some researchers (e.g. in China, DEXA is ranked higher than DAWAK by the Chinese Computer Federation).
Personally, I enjoy the DEXA and DAWAK conferences. There are not so big but the paper are overall of good quality. Also, there is often some special journal issues associated with these conferences. I have previously attended these conferences several times. My report about previous editions can be found here: DEXA and DAWAK 2016, DEXA and DAWAK 2018, and DEXA and DAWAK 2019.
This year, 71 papers were submitted to DaWaK 2021. 12 papers were accepted as full papers and 15 as short papers. Thus, 16% is the acceptance rate for the full papers and 35% for both full and short papers.
The best papers of DAWAK were invited to submit an extended version in a special issue of the Data & Knowledge Engineering (DKE) journal.
For DEXA, I did not see the information about the number of submission in the front matter of the Springer proceedings. Usually this information is provided for conferences published by Springer. But this time, it is just said that “the number of submissions was similar to those of the past few years” and that “the acceptance rate this year was 27%“. To estimate the number of submissions, I counted that there is about 67 papers in the proceedings. Thus, the number of submissions would be about 67 / 27 * 100 = 248 submissions.
Thus, this would be a 25% increase from last year, since in 2020, there was 197 submissions, in 2019, there was 157 submissions, and in 2018, there was 160 submissions.
On the first day, there was the opening session.
The program of the conference was presented, as well as the different organizers. It was said that this year there is a panel and five keynote speakers. Attendees were also asked to scan a QR during the opening to indicate their location, which generated the following word cloud:
The paper presentations were done online using the Zoom software. There was a lot of interesting topics. Here is a screenshot of the first paper session on big data from DEXA 2021:
I presented the paper of my student about episode rules. During that session, there about a dozen people and there was some interesting questions. Due to the schedule and time different, I was not able to attend all the paper presentations that I wished to attend, but I saw some interesting work.
Papers about pattern mining
This year, again, there was several papers about pattern mining at DEXA and DAWAK. Since it is one of my research area, I will report about these papers:
- P. Revanth Rathan, P. Krishna Reddy, Anirban Mondal: Improving Billboard Advertising Revenue Using Transactional Modeling and Pattern Mining. 112-118
- Yinqiao Li, Lizhen Wang, Peizhong Yang, Junyi Li: EHUCM: An Efficient Algorithm for Mining High Utility Co-location Patterns from Spatial Datasets with Feature-specific Utilities. 185-191
- Yangming Chen, Philippe Fournier-Viger, Farid Nouioua, Youxi Wu: Mining Partially-Ordered Episode Rules with the Head Support. 266-271 [ppt] (paper from my team)
- Xin Wang, Liang Tang, Yong Liu, Huayi Zhan, Xuanzhe Feng: Diversified Pattern Mining on Large Graphs. 171-184
- So Nakamura, R. Uday Kiran, Likhitha Palla, Penugonda Ravikumar, Yutaka Watanobe, Minh-Son Dao, Koji Zettsu, Masashi Toyoda: Efficient Discovery of Partial Periodic-Frequent Patterns in Temporal Databases. 221-227
- Amel Hidouri, Saïd Jabbour, Badran Raddaoui, Mouna Chebbah, Boutheina Ben Yaghlane: A Declarative Framework for Mining Top-k High Utility Itemsets. 250-256
On overall, it was a good conference. It is not so big but well-organized and with some good papers. I will certainly continue to send papers to that conference in the following years, and hopefully I can attend that conference in person next time. That would be much more interesting than a virtual conference because one of the best part about academic conferences is to be able to meet people and talk face to face.
Philippe Fournier-Viger is a distinguished professor of computer science and founder of the SPMF open-source data mining library, which offers over 200 algorithms for pattern mining.