Brief report about the IEA AIE 2022 conference

This week, I am attending the 35th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems conference (IEA AIE 2022) as a member of the organization committee. I will give a brief report about the conference.

What is IEA AIE?

IEA AIE is a well-established conference (35 years already!) about applied artificial intelligence, that is not only the theoretical aspects of artificial intelligence but also the applications. It is a medium-sized conference with an audience that is very international with authors from all over the world. I have attended this conference many times, and it has always been interesting. You can see my report about previous editions of the conference here: IEA AIE 2016IEA AIE 2018IEA AIE 2019 , IEA AIE 2020, and IEA AIE 2021.


This year, the conference received 127 paper submissions, from which 65 have been accepted as full papers, and 14 as short papers. The proceedings are published by Springer. All the papers have been reviewed by at least 3 members from the program committee. The program committee consists of 73 persons from 23 countries. I was one of the two PC chairs this year.

Opening ceremony

The IEA AIE 2022 conference was held in Kitakyushu City in Japan in hybrid mode. I think the majority of attendants were online but there was still many people attending in person. On the first day, there was the opening ceremony. The conference was introduced including the program and other aspects.

It was announced that IEA AIE 2023 will be held in Shanghai, China. The call for papers of IEA AIE 2023 was presented as well as an overview of the organization and other details. Here is a screenshot of the call for papers of IEA AIE 20223 (

The deadline for submitting papers to IEA AIE 2023 is in December 2022.

Paper presentations

There was several paper presentations, covering many different topics such as: industrial applications, health informatics, optimization, video and image processing, natural language processing, agent and group-based systems, pattern recognition, security.

Here is screenshots from some presentations, that I have attended.

This is a paper about air pollution, which use image processing combined with a periodic pattern mining algorithm to obtain good detection:

Below is a paper from my collaborators about parallel high utility itemset mining based on Spark. In that paper some good results are obtained where a parallel version of EFIM and d2HUP provides some good speed-up (up to 20 times) over the sequential versions of those algorithms for mining high utility itemsets.

There was also an interesting paper about weighted sequential pattern mining in uncertain data:

There was also many other papers that I have listened too. I will not report on all of them.

Keynote talks

At IEA AIE 2022, there was two keynote talks. The first keynote was by Prof. Tao Wu from Shanghai University of Medicine & Health Sciences about health informatics. I miss the first half of the keynote, so I will not report on the details but it seems that the audience enjoyed very much that presentation.

The second keynote talk was by Prof. Sebastian Ventura from University of Cordoba, Spain about Improving Predictive Maintenance with Advanced Machine Learning. He talked about how to build models and systems to prevent failure from happening in industrial systems by doing maintenance in advance (predictive maintenance – PdM). He explained that various techniques can be used such as for outlier detection and classification. Prof. Ventura told that he is doing a project for the maintenance of military vehicles. Following the talk, there was a good discussion with conference participants. Prof. Ventura explained that building simple models is good but it is not necessarily the most important. A complex model can be acceptable if it is explainable. In fact, he said that it is more important to have explainable models because in real-applications, models often need to be verified by domain experts. Here are a few slides from that talk about the introduction:

Here are some slides about potential data mining techniques that can be used:

And here are some techniques that have been used in the specific project for predictive maintenance of vehicles:

Here are some challenges and open problems and the conclusion from the talk:

If you are interested by this topic, you may also check the survey paper published recently by Prof. Ventura:

A. Esteban, A Zafra & S. Ventura. Data Mining in Predictive Maintenance Systems. WIREs DMKD.

Best paper awards

Several awards have also been announced at the conference. The selection was made by looking at the scores during the review process but also by analyzing carefully the reviews and the papers.

  • Best student paper award
    Question Difficulty Estimation with Directional Modality Association in Video Question Answering
    Bong-Min Kim and Seong-Bae Park
  • Best theory paper award
    Evolution of Prioritized EL Ontologies 
    Rim Mohamed and Zied Loukil and Faiez Gargouri and Zied Bouraoui
  • Best application paper award
    A Generalized Inverted Dirichlet Predictive Model for Activity Recognition using Small Training Data
    Jiaxun Guo and Manar Amayri and Wentao Fan and Nizar Bouguila
  • Best special session paper award
    An Oriented Attention Model for Infectious Disease Cases Prediction
    Peisong Zhang and Zhijin Wang and Guoqing Chao and Yaohui Huang and Jingwen Yan

There was also an award for the best technical presentation given to the best presenter who attended the IEA AIE conference in person.


This was a good conference. Looking forward to IEA AIE 2023 next year in Shanghai, China.

Philippe Fournier-Viger is a full professor working in China and founder of the SPMF open source data mining software.

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