Is it a good to change research area?

Posted on 2020-11-17 by Philippe Fournier-Viger

In this blog post, I will talk about changing to another research area for researchers and what it implies. Moreover, I will talk about what is a good research area, and the importance of continuity for researchers. I will also discuss about my own experience related to changing research areas.

Time for Change Sign With Led Light

Reasons for changing research areas

There are several reasons for considering a change of research area at different points in the career of a researcher, and also for graduate students. Some reasons are:

  • Changing for a more popular research area. One may wants to work on a more popular research area to follow some new trends. For example, in computer science, one may want to change from a more traditional research area like compiler design to a more popular topic like big data, data science, the internet of things, sensor networks, or machine learning. By following some trends, it may be easier to find a job, get some research funding, get some industrial collaboration projects, publish papers in special issues or workshops, get more citations and have a greater research impact, etc.
  • Personal interests. A researcher may want to try something new or he may feel more interested into a different research area to explore new problems and learn other things.
  • Joining a research team that works on a specific research area. For example, a professor joining a university may want to slightly change research area to integrate with a research team that is specialized on a research topic.
  • Changing for a research area where it is easier to publish articles. For many universities, publishing papers is a performance evaluation criterion. In this context, some researcher will want to work on topics where it is easier to do new contributions, carry experiments and publish articles.

Those are some of the key reasons that a researcher may consider. Whether those are good reasons or not depends on each case. For example, a researcher may not care about working on a popular topic but may rather work on something that he really likes.

I will talk about my own experience as example. In my early research career, I have been working on intelligent tutoring systems and cognitive modelling but found that it was a difficult topic for carrying research as it required to do experiments with people to evaluate my proposals, which was very time-consuming. Moreover, the research community around intelligent tutoring systems is quite small (maybe a few hundred people), so the possibility of having a great research impact was in my opinion limited. Also, I have a personal interest in algorithm design and optimization. Hence, at the end of my Ph.D., I started to switch from this research area towards doing research on data mining. Nowadays, my research area is data mining, and more specifically pattern mining. I think it was a good decision in my case because data mining is a more popular research area, I like this field, and it is easier to do research and write papers, and there is more job opportunities. Besides, by working at a more fundamental level (algorithm design) rather than at the level of applications, I can have a greater research impact. For instance, my algorithms are not limited to only be applied in intelligent tutoring systems but can be used in other fields. If I would keep working on a narrow topic with a small research community, it would be harder to get citations (not so important, but it is still a performance evaluation criterion at some universities).

What is a good research area?

There is no absolute answer to this question. But a researcher can try to answer these questions to assess a research area:

  • Is this research area that is interesting for you?
  • Is this a research area where you can make some good contributions?
  • Is this related to your current expertise? This is important to avoid starting again from zero… If you change to a research area that is somewhat related to your current research area, it may be better.
  • Is this a popular research area?
  • Can you get some special opportunities in that research area (join a team, get a job, funding, etc.)?

Those are some important criteria but it is not necessary to meet all there criteria.

The importance of continuity
Changing research area can be good. However, continuity is also important in the career of a researcher. Changing too often from one research area to another is not good. It will show a lack of focus and it may seem that the researcher is a specialist of nothing. It is better for the career of a researcher to focus on a specific research area and make several good contributions in that area over the years to become more and more famous in that area and benefit from this. As a researcher continue to work in the same area, it becomes easier (and faster) to make better research contributions and write papers. The researcher can also build many collaborations with other researchers over the years, and it becomes also easier to obtain research funding in a research area where you have published many papers.

In my opinion, the best time to change research area is at the begining of the career of a researcher. For example, I gradually changed towards data mining towards the end of my Ph.D. and now mostly only do data mining research. Ten years later, I would not change research area again, because now, I am well-established researcher in that area, and I am also happy to work on this. If I would change again to another research area, then it would become harder to publish papers, obtain grants, and I would have to learn many things again. So my focus is on data mining, but I am still sometimes work on other topics as side-projects. 😉

Changing a research area also requires some planning and to think ahead of time. It is also better to gradually change toward the new research area, if possible.

Conclusion

In this blog post, I talked about changing research areas as it is a concern for several researchers especially early in their career. Hope that it has been interesting. If you would like to share your own experience or have comments related to this, please post in the comment section below!

—-
Philippe Fournier-Viger is a professor of Computer Science and also the founder of the open-source data mining software SPMF, offering more than 170data mining algorithms.

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How to write the cover letter for a journal paper?

Posted on 2020-11-13 by Philippe Fournier-Viger

In this blog post, I will talk about how to write a cover letter for a journal paper. This is an important topic for researchers swho submit research papers to journals, as many journals require to write and submit a cover letter with the paper.

man writing on paper

What is the purpose of the cover letter?

A researcher write a cover letter to inform the editor of the journal that he is submitting a paper. The cover letter should be adressed to the editor of the journal.

The content of cover letters can vary and some journals have specific requirements about the content of a cover letter. Thus, before writing a cover letter, it is important to check if there are some requirements. Some journals also do not require to write a cover letter.

A cover letter typically contains the following content:

  • The title of the paper
  • One or two sentences to explain what is the topic of the paper and why it is suitable for the journal (if not obvious)
  • A statement to say that the work is original and has not been submitted to other journals
  • A statement to say that all authors have agreed to the submission
  • The list of all author names

Personally, I think that a cover letter does not need to be very complicated. But at least a cover letter should not contain errors and should be written in a polite way. If a cover letter contains several English errors, then it may give a bad impression to the editor.

Two examples of cover letters

Here is a first example of cover letter that I have used recently:

Dear editor,

We wish to submit an original research article entitled “NAME_OF_THE_PAPER” for consideration by NAME_OF_THE_JOURNAL.

I would like to declare on behalf of my co-authors that this work is original and has not been published elsewhere, nor is it currently under consideration for publication elsewhere. Moreover, we have no conflicts of interest to disclose.

We believe that this manuscript is appropriate for publication by NAME_OF_THE_JOURNAL because it fits with the principal objectives of the journal by proposing a new solution to one important research problem in pattern mining. More precisely, a new efficient solution is proposed for the problem of XXXXXXX.

We deeply appreciate your consideration of our manuscript, and we look forward to receiving comments from the reviewers. If you have any queries, please don’t hesitate to contact us at: EMAIL_ADDRESS

Thank you for your consideration of this manuscript.

Sincerely,

CORRESPONDING AUTHOR NAME
CORRESPONDING AUTHOR AFFILIATION
CORRESPONDING AUTHOR EMAIL

And here is another example that is slightly different:

Dear editor,

We are submitting this paper proposing a new algorithm to …….. , named ……. . This is an important problem in the context of …….. Unlike previous work who focused on ……. we propose an algorithm that consider …. . To develop an algorithm for that measure, novel theoretical results are presented, …… We show in experiments that the proposed outperforms the compared algorithms in terms of execution time and memory usage 

This manuscript is the authors’ original work and has not been published. Moreover, it has not been submitted simultaneously elsewhere. 

All authors have checked the manuscript and have agreed to the submission.

Thanks for handling this manuscript. We are looking forward to receive feedback from the evaluation process.

Best regards,

AUTHOR NAME
AUTHOR AFFILIATION
AUTHOR E-MAIL

Conclusion

In this blog post, I have discussed how to write a cover letter for a journal paper, and given some examples. You may use this as basic templates for writing your own cover letters or make your own while keeping the key information that a cover letter should have. Hope that this will be helpful.

—-
Philippe Fournier-Viger is a professor of Computer Science and also the founder of the open-source data mining software SPMF, offering more than 170data mining algorithms.

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How to find a good thesis topic in Machine Learning?

Posted on 2020-11-04 by Philippe Fournier-Viger

In this blog post, I will talk about how to find a good thesis topic on machine learning. This is an important question for many students that are required to select a topic for their research and want to work on machine learning. Choosing a good research topic is a critical step in the research process to ensure the success of the research and for publishing good papers.

What is a good research topic?

A good research topic is a research problem that is:
(1) novel,
(2) challenging to solve (cannot just be solved by applying existing techniques) but not too challenging or long,
(3) useful (otherwise, there is no reason to do the research), and
(4) a problem that is interesting for other researchers or has applications.

It should also be clear that a research topic is not equal to doing a programming or software development project. Just solving a software development problem is generally not research. Research is about solving a novel and difficult problem that requires to develop some inovative solution.

How to find a good research topic on machine learning?

To find a good research topic, it is important to know what other researchers have done in recent years. Thus, to select a topic, one should first read papers in good journals and conferences to see what other researchers have been doing. By reading recent papers, one can try to think about the limitations of these studies and what could be improved, or what other researchers have not done yet (because there is no point to do the same thing again). Reading the literature requires some time and is not so easy to do but is very important to choose a good topic. For the young students, it is recommended to ask advices from their supervisor during this step. The supervisor should be able to suggest some good papers to read as starting point and to validate the research topic ideas. When reading paper, one can pay attention to the related work section and conclusion, which sometimes highlight some limitations of previous studies and can give some ideas for research.

Generally, it is a good to work on some research area that other researchers are interested in rather than working on some obscure problems that have few applications.

After finding some idea that is novel, it is also important to keep searching for papers to make sure that the idea is really novel and no one has done it before. If someone did it already, it is better to find this issue as early as possible to avoid wasting time on pursuing a research idea that has been done before. When searching for other papers, it is also important to find the right keywords for searching. Some research topic may have already been studied but with a different name. Thus, when searching for papers, it is important to try various keywords and to keep searching to make sure that the literature has been checked carefully.

How to describe your research topic?

A common misconception about choosing a research topic is to think that just choosing a title is good enough for choosing a research topic. But it is not. A research topic should be defined clearly and with more details.

For example, a topic title like ‘machine learning for image processing’ is too broad and does not mean much about what one would like to do. What kind of machine learning technique? What kind of image processing task? And what is the originality? All of this could be explained more clearly with a more detailed description.

To clearly define your research topic, I recommend to write some text explaining:
– the title,
– why the problem is important?
– what are the limitations of previous studies that this research will address?
– why that research problem is challenging?
– and give a sketch of some possibilities  for solving the problem.

If you can answer the above questions, then it means that you have carefully thought about your research topic.

You may also ask some senior researchers to look at your research topic to confirm that it is a good topic.

Conclusion

In this blog post, I have discussed the problem of searching for a research topic in machine learning. Hope this has been helpful. If you have some comments, please leave them in the comment section below.

—-
Philippe Fournier-Viger is a professor of Computer Science and also the founder of the open-source data mining software SPMF, offering more than 170data mining algorithms.

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Brief Report about the PKDD 2020 conference

Posted on 2020-10-22 by Philippe Fournier-Viger

In this blog post, I will talk about the ECML PKDD 2020 conference, that was held from the 14th to 18th September 2020. This post will be a little bit brief because I did not attend the whole conference but just a few presentations.

What is PKDD?

The PKDD conference is the number one data mining and machine learning conference in europe. This year, it was the 31st edition of this conference. The PKDD conference proceedings are published by Springer in the Lecture Notes in Computer Sciences (LNCS) series, which gives good visibility to the papers. Moreover, it is noteworthy that workshop papers are also published in Springer LNCS volumes.

Due to the coronavirus pandemic, the conference was held online but was supposed to be held in Ghent Belgium.

Videos

Many of the papers and videos have been made available online on the website of the conference: https://slideslive.com/ecmlpkdd2020/main-track-research-track

I have been watching a few of them, and it has been very interesting, as papers of this conference are high quality papers.

Program

The PKDD 2020 conference has 5 keynotes, an applied data science track, a research paper track, industry track, demo track, workshops, tutorials, and a journal paper track.

Opening ceremony

I will here report important information that was presented during the PKDD 2020 opening ceremony.

There was about 1000 persons involved in the program committee for reviewing papers, and about 1000 attendees. It was explained that hundreds of people were recruited this year to join the program committee due to the increase of papers in machine learning.

In the research track, this year 687 papers were submitted. From that, 131 were accepted. Thus, the acceptance rate was 19.1 %. Here is a few slides about the research track:

For the Applied Data Science track, 235 papers were submitted, and 65 accepted. Thus, the acceptance rate was 28 %, which is quite higher than the research track. Here is the number of papers by topic:

For the demo track, 23 papers were submitted, and 10 were accepted, for an acceptance rate of 43 %. Some information about this track:

Here are the statistics about the papers submitted to the DMKD or Machine learning journals for the journal track :

For the industry track, the acceptance rate was about 50%:

This is about the diversity of authors in terms of regions:

Here are the best data mining papers:

And this was the best applied data science paper:

Pattern mining papers

As I am interested by the topic of pattern mining, I have made a list of the main papers on this topic published in the PKDD 2020 conference:

  • Maximum Margin Separations in Finite Closure Systems
    Florian Seiffarth (University of Bonn); Tamas Horvath (University Bonn); Stefan Wrobel (Fraunhofer IAIS & Univ. of Bonn)
  • Discovering outstanding subgroup lists for numeric targets using MDL
    Hugo Manuel Proença (LIACS); Peter Grßnwald (CWI); Thomas Bäck (LIACS); Matthijs van Leeuwen (LIACS)
  • A Relaxation-based Approach for Mining Diverse Closed Patterns
    Arnold Hien et al.
  • OMBA: User-Guided Product Representations for Online Market Basket Analysis
    Amila Silva (The University of Melbourne); Ling Luo (The University of Melbourne); Shanika Karunasekera (The University of Melbourne); Christopher Leckie (The University of Melbourne)

Conclusion

That is all for my report about the PKDD 2020 conference. The report is not very long because of my busy schedule. Hence, I only watched a few presentations from the conference. Hope this report has still been interesting.

—-
Philippe Fournier-Viger is a professor of Computer Science and also the founder of the open-source data mining software SPMF, offering more than 170data mining algorithms.

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Why it takes so long for a journal paper to be reviewed?

Posted on 2020-10-22 by Philippe Fournier-Viger

Today, I will talk about the review process of journal papers and why it sometimes take so much time for a paper to be reviewed. It is a question that is often asked by young researchers, who are sometimes impatiently waiting for their journal papers to be published to graduate. I will first give a brief overview of the review process of journal papers and then explain what can go wrong.

An overview of the review process

The main steps of the review process are:

  • STEP1: Initial screening and assignment to an editor: After submitting a paper to a journal, there will typically be a first screening of the paper performed by an assistant working for the journal. This is done to check the format of the paper and if there are some other issues such as plagiarism or if the paper has been submitted twice. If the paper does not pass this screening, it may be rejected directly. Otherwise, it will be send to an editor.
  • STEP2: Inviting reviewers: The editor will then look at the manuscript and invite some appropriate reviewers to review the paper. The reviewers will either accept or decline to review the paper. Usually, a minimum number of reviewers is required. Thus, if there is not enough reviewers, the editor will receive a notification and will have to invite more reviewers until the minimum number of reviewers is attained. To speedup that process, an editor may pre-select a list of alternate reviewers that may be automatically invited when a person decline to review.
  • STEP3: Reviewing the paper: The third step which is partly done in parallel to the second step is that reviewers will review the paper and submit their reviews. The editor will give them a deadline that is will vary depending on the journal. For example, some journal will give 1 or 2 months.
  • STEP4: The decision: When all the reviews are completed, the editor will receive a notification. Then the editor will read the reviews and submit his decision such as to accept, reject, or request minor or minor revisions of the paper. It is also possible that the editor does not wait for all reviews to take a decision. For example, if the editor needs 4 reviews but two of them are “reject”, he will likely reject the paper without waiting for the 4 reviews.
  • STEP5: Sending the notification: The decision will be sent to the authors. Then, if a revision is required, the authors will submit the revision and the process will start again from STEP1. If the paper is accepted, it will go in production. And if the paper is rejected, it will be the end.

What can go wrong?

Several things can go wrong an delay the review process:

  • The editor is busy and waits to invite reviewers: A first problem is that after the editor receives the paper, he may not invite reviewers right away because he is busy with other things. Some editors are quite fast (for example, I always assign reviewers whithin 24 hours) but others will take a few weeks (this happened to me a few times).
  • Many reviewers decline to review the paper: A second problem is that it is sometimes difficult for the editor to find suitable reviewers for a paper that agree to review. The reason is that some reviewers are busy (e.g. they already accepted to review other papers or have other things to do), have a conflict of interest or are just not interested in reading the paper. Thus, a reviewer may decline to review the paper. Hence, the editor may need to invite morereviewers to review the paper. Sometimes more than a dozen potential reviewers may have to be invited before enough reviewers will accept. For the papers that are on very specialized or unpopular topics, it may be more difficult.
  • Some potential reviewers take too much time to accept or decline to review: When a researcher receives an invitation to review from an editor, he will typically answer quickly. However, in some cases, the researcher does not answer and the editor may give up to 14 days before retracting the invitation. If the potential reviewer does not answer, the editor need to find a replacement. Thus, the task of finding enough reviewers will in some case take more than a month.
  • Reviewers are late: This is another major problem. Although reviewers often have 1 month or more to review a paper, they are sometimes very busy and will submit their review not just late but very late. For example, some reviewers are late by more than 30 days… and this is not very rare. In such situation, the editor can either decide to wait or send more reminders to the reviewer or remove him and take decision without him, or start again to invite some new reviewers (which may take more time!)
  • The editor take time to handle the reviews: Even after the reviewers have submitted their reviews, the editor may still be busy and wait before submitting his decision. In the worst case, I have seen some editor taking a few weeks for submiting their decision.
  • A combination of the above problems: And of course, all the above problems may appear at the same time. If someone is really unlucky, the editor may take a lot of time before inviting reviewers, many reviewers may decline to review and they may take much time to do so. Then, the reviewers may be late or even never submit their reviews. Hence, the editor may have to find some new reviewers again and they could be late again, and then the editor may be late to handle the decision.
  • Problems during the second round of review: Besides the above problems, some other problems may occur after the first round of review. For example, during the second round of review, the editor will typically invite the same reviewers from the first round. However, reviewers from the first round may not accept to review the paper again. This happens quite frequently because the reviewers are busy or for other reasons. In that case, the editor may have to invite some new reviewers, which may take extra time. And these new reviewers may ask for more changes in the paper, which may further delay the overall process.

Conclusion

In this blog post, I talked about some common reasons why the reviewing process may be long for some journal papers. As an author, there is not much that one can do to make this process faster. Hope that it has been interesting. If you have any comments or questions, you may post them below in the comment section.

—-
Philippe Fournier-Viger is a professor of Computer Science and also the founder of the open-source data mining software SPMF, offering more than 170data mining algorithms.

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(video) Top-K Cross-Level High Utility Itemset Mining

Posted on 2020-10-18 by Philippe Fournier-Viger

Today, I will share a video of our upcoming paper presentation about top-k cross-level high utility itemset mining that we will present at the UDML 2020 workshop at ICDM 2020.

In this paper, we present a novel algorithm named TKC for discovering cross-level high utility itemsets (CLHUIs) in a database of transactions while considering a taxonomy of items. A taxonomy means that items are organized into categories and sub-categories. Moreover, to make it easier to find interesting patterns, we let the user directly specify the number k of patterns to be found. The TKC algorithm returns the top-k cross-level high utility itemsets that have the highest utility.

Here is the video (MP4 format, 20 minutes):


VIDEO LINK: https://www.philippe-fournier-viger.com/tkc_the_video.mp4

And this is the reference of the paper, including the PPT presentation:


Nouioua, M., Wang, Y., Fournier-Viger, P., Lin, J.-C., Wu, J. M.-T. (2020). TKC: Mining Top-K Cross-Level High Utility Itemsets. Proc. 3rd International Workshop on Utility-Driven Mining (UDML 2020), in conjunction with the ICDM 2020 conference, IEEE ICDM workshop proceedings, to appear. [ppt] 

The datasets and source code will be made available soon on the SPMF data mining library, wihch offers more than 170 algorithms for pattern mining.

Besides, if you are interested by this topic, you can also check another recent paper on this topic by our team. The paper below presents the CLH-Miner algorithm for cross-level high utility itemset mining. It was used as basis to develop the TKC algorithm.


Fournier-Viger, P., Yang, Y., Lin, J. C.-W., Luna, J. M., Ventura, S. (2020). Mining Cross-Level High Utility Itemsets. Proc. 33rd Intern. Conf. on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA AIE 2020), Springer LNAI, pp. 858-871. [ppt]

Hope you will enjoy this video. I will post more videos soon about recent papers. And also, we am currently preparing the source code and datasets to release them soon.

—-
Philippe Fournier-Viger is a professor of Computer Science and also the founder of the open-source data mining software SPMF, offering more than 170data mining algorithms.

Posted in Pattern Mining, Utility Mining, Video | 1 Comment

More problems on IONOS web hosting… 4 days of downtime!

Posted on 2020-10-05 by Philippe Fournier-Viger

A month ago, I had some big problems with my website hosted by 1and1 ionos. The database was seemingly reverted to three back and I lost all the posts from the last three years! This week, I got more problems with 1and1 (also known as 1&1 IONOS). I have several days of downtime due to their database server going offline. I am am not happy with the service. Here is the story.

October 1st 2020. Recently, I noticed that my data mining forum (https://forum2.philippe-fournier-viger.com/ ) hosted on 1and1 Ionos went offline due to a technical problem. When I connected to the website, it has shown this error:

IONOS database problem

First, I thought that the problem was something going wrong on my website or that I may have been hacked. So, I used the 1and1 Ionos control panel to reset the password of the database and I also downloaded the sample PHP script from them to connect to the database to ensure that it was not a problem of my website:

But that script also failed to connect. Thus, I clicked on the Ionos control panel to see the database directly through PHPMyAdmin:

Image insĂŠrĂŠe

Then, I got that error indicating that the database is offline:

IONOS database problem

Here, the message is in Chinese, but basically it says:

mysqli_real_connect(): (HY000/1045): Access denied for user ‘dbo276830812’@’10.72.2.8’ (using password: YES)

PhpMyAdmin tried to connect to the MySQL server, but the server refused to connect. You should check the host, user name, and password in the configuration file and make sure that the information is consistent with the information given by the MySQL server administrator.”

So obviously, since I cannot even connect to the database through the 1and1 control pannel, it is a problem on the side of 1and1 Ionos. And this is why my website has gone offline.

October 2nd: I sent an e-mail to 1and1 Ionos to inform them about the problem through the customer support e-mail at 1:09 AM on October 2nd (Beijing Time). Here is their answer promising that I would be answered whithin 48 hours:

October 4th: I still did not receive any news from 1and1 Ionos and the website is still down because of the database being unavailable. So on the evening, I contacted the 1and1 IONOS customer service again through the live chat to see what is going on and the representative told me that my request is in the customer support system and has been escalated. He also told me that they are sorry for the inconvenience, and told me to wait a bit and he would check something in the system. Then for some reason (poor internet connection?), the customer support live chat window closed. So I decided to wait until tomorrow.

October 5th: About 10 hours later, it is already more than four days that the website is down due to this technical problem… Finally, the problem was fixed and got some answer from the customer service:

In that answer, 1&1 claims that the host name was wrong. However, I had updated it on October 1st to see if this was the problem. Moreover, I also tested conneting directly to the database through PHPMYADMIN from the 1&1 control panel and it was also down. So this was certainly not the problem. Thus, it seems that they do not want to admit that the problem was on their side and try to find some excuse about this to put the blame on the customer… This is similar to when my database was reverted to 3 years ago in August and I lost many blog posts on another website hosted on their service. They also did not want to say where the problem came from but it seemed to be obviously coming from them….

So, I am happy that the problem is fixed but I am still not very happy about their service. My data mining forum had been down for several days and when you pay for a hosting provider, you expect 99% availability, or at least a quick fix in case of technical problem from their side.

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A brief report about the IEA AIE 2020 conference

Posted on 2020-09-22 by Philippe Fournier-Viger

In this blog post, I will write a brief report about the 33rd International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA AIE 2020), held in Kitakyushu, Japan from the 22nd to 25th September 2020.

What is IEA AIE 2020?

The IEA AIE 2020 is a well-established academic conference that has been running for 33 years. It is about artificial intelligence, and it attracts many papers about the applications of intelligent systems.

I have personally attended this conference many times in the past (IEA AIE 2009, IEA AIE 2010, IEA AIE 2011, IEA AIE 2014, IEA AIE 2016, IEA AIE 2018, IEA AIE 2019), and have 13 papers in its proceedings.

This year, I am attending IEA AIE 2020 as author but also as program chair. The organizers this year are:

Proceedings of IEA AIE 2020

This year, 119 papers have been submitted to the conference. Each paper has been reviewed by at least 3 reviewers. The Program Committee who evaluated the papers is composed of 82 researchers from 36 countries.

A total of 62 full papers were accepted and 17 short papers. All of those were published in the Springer proceedings. Moreover, an additional 9 poster papers were published in a separated poster proceedings with ISBN.

The papers covered many applications to real-life problems such as: •engineering, science, •industry, •automation •robotics, •business and finance, •medicine and biomedicine, •bioinformatics, •cyberspace, •human-machine interaction.

This year, in the new format of the IEA AIE conference, some special sessions were organized. A special session is like a special track about a specific topic of interests. All papers from the special track are published in the main conference proceedings. Here is the information about the two tracks:

Best paper awards

Moreover, this year, four types of awards are announced during the conference:

  • Best paper award: Dolly Sapra, Andy D. Pimentel: Constrained Evolutionary Piecemeal Training to Design Convolutional Neural Networks.
  • Best theory paper award: Fan Zhang et al.
    A new integer linear programming formulation to the inverse QSAR QSPR for acyclic chemical compounds
  • Best application paper award: Wei Zhang and Chris Challis
    Automatic identification of account sharing for video streaming services
  • Best special session paper award: Wei Song, Lu Liu, Chaomin Huang
    TKU-CE: Cross-Entropy Method for Mining Top-K High Utility Itemsets

These awards were selected by a committee based on review scores and a discussion of the top papers. To ensure that the process is fair, papers from the organization committee members were excluded from receiving awards.

A partly virtual conference

Due to the coronavirus pandemy around the world, the conference was held virtually and also on site in Japan at the same time. This required some special organizations from the local organizers and was very well done. I was happy to saw friends in the conference.

Day 1 – Opening session, keynotes and regular papers

In the opening session of the conference, the conference was presented. Each organizers gave some words about the conference. Then, there was two keynote speeches : one by Prof. Tao Wu about healthcare, and the other by Prof. Ee-Peng Lim about AI for social goods.

The talk of Prof. Lim was very interesting as he talked about two projects that can have a positive implications for the society. The first one was about a probabilistic model of the labor market in Singapore. The second one was about an application that can let users take picture of their food to keep track of what they are eating. The system FoodAI can be tested on this website: https://foodai.org/ Here is a few slides from this presentation.

In his conclusion, Prof. Lim also talked about three challenges for the development and adoption of proposed models.

The keynote was followed by several paper presentations on various topics.

Day 2 – regular papers + keynote talks

On the second day, there was more paper presentations and also two keynote talks (one by Prof. Bo Huang and one by Prof. Enrique Herrera Viedma).

The keynote of Prof. Enrique Herrera Viedma was about group decision making, that is how a group of expert can reach an agreement to take decisions.

Generally, group decision making is reached through a concensus reaching process which requires discussion between experts and involve multi stage negotiation. Here are a few slides, describing the main process:

He explained that nowadays group decision making is done in a new context, with social networks and Web 2.0 tools.

Then, he discussed in more details about properties of social networks and how sentiment analysis can play a role in decision-making models. Here are a few of the important properties of social networks:

Sentiment analysis can be used in group decision making to understand how a user feels about a particular topic, and in particular the preferences of experts about different alternatives. Here are some details:

Here is an overview of the proposed group decision making based framework

Then, there was more details but I will not report on everything.

An upcoming special issue in the Applied Intelligence journal

Another great thing this year at IEA AIE is that there will be a special issue in the Applied Intelligence journal (Springer, Q2). The best papers of the conference will be invited for an extension in the special issue. Details will be announced after the conference.

Next year… IEA AIE 2021… in Kuala Lampur

It was announced that the IEA AIE 2021 conference will be held next year in Kuala Lampur (Malaysia).

The website of IEA AIE 2021 is already online at http://ieaaie2021.wordpress.com/ Here are the key dates related to this conference:

Day 3 and 4 – More paper presentations

On the third and fourth days, there was more paper presentations.

Pattern mining papers

This year, there was 7 pattern mining papers, which shows that it is a popular topic at this conference. These papers cover topics such as periodic itemset mining, and high utility itemset mining. Since this is a topic of interest for me and to several readers of this blog, here is the list of papers:

  • TKU-CE: Cross-Entropy Method for Mining Top-K High Utility Itemsets
    Wei Song, Lu Liu and Chaomin Huang
  • Mining Cross-Level High Utility Itemsets
    Philippe Fournier-Viger, Ying Wang, Jerry Chun-Wei Lin, Jose Maria Luna and Sebastian Ventura [ppt]
  • Maintenance of Prelarge High Average-Utility Patterns in Incremental Databases
    Jimmy Ming-Tai Wu, Qian Teng, Jerry Chun-Wei Lin, Philippe Fournier-Viger and Chien-Fu Cheng
  • Efficient Mining of Pareto-front High Expected Utility Patterns
    Usman Ahmed, Jerry Chun-Wei Lin, Jimmy Ming-Tai Wu, Youcef Djenouri, Gautam Srivastava and Suresh Kumar Mukhiya
  • TKE: Mining Top-K Frequent Episodes
    Philippe Fournier-Viger, Yanjun Yang, Peng Yang, Jerry Chun-Wei Lin and Unil Yun
  • Parallel Mining of Partial Periodic Itemsets in Big Data [ppt]
    C. Saideep, R. Uday Kiran, Koji Zettsu, Cheng-Wei Wu, P. Krishna Reddy, Masashi Toyoda and Masaru Kitsuregawa
  • A Fast Algorithm for Mining Closed Inter-Transaction Patterns
    Thanh-Ngo Nguyen, Loan T.T. Nguyen, Bay Vo and Ngoc-Thanh Nguyen

Conclusion

I have enjoyed the conference. Next year, IEA AIE 2021 will be in Malaysia, and then IEA AIE 2022 in Japan.

—
Philippe Fournier-Viger is a computer science professor and founder of the SPMF open-source data mining library, which offers more than 170 algorithms for analyzing data, implemented in Java.

Related posts:

Key Papers about High Utility Itemset Mining
A brief report about the IEEE DSAA 2022 conference
What is a Closed Itemset and Why is it Useful?
Posted in artificial intelligence, Conference, Data Mining | Tagged , , , , , , , | 4 Comments

The Imposter Syndrome in Academia

Posted on 2020-08-27 by Philippe Fournier-Viger

In this blog post, I will talk about something that many students or researchers have or are experiencing in academia, which is called the imposter syndrome. It is the feeling of not being worthy of having achieved some success or being in a given position. For example, a new PhD student accepted in a top university may feel that he was just lucky and did not really get accepted because of his skills or efforts. A professor may similarly feel that he received funding but that it is undeserved. The imposter syndrome is something very common in academia. Many people have experienced it at some point in their career.

Personally, when I was first admitted in the master degree in computer science more than 15 years ago, I felt that there was still some gaps in my knowledge. For example, I thought that I had not learnt enough about some topics in computer science or mathematics during the bachelor degree. Although I was a reasonably good programmer, it appeared to me that some other students were better. Moreover, another question that I had when starting the master degree was: Even if I am a good student, will I be successful at research? This is a question that many students have because doing research is something new at that stage.

Then, during the master and Ph.D degree, I published several papers on e-learning and started to attend academic conferences. But when attending the conferences, I felt sometimes that my knowledge of the field was not so deep compared to that of many experts there.

Later, I changed my research direction towards data mining and became very good in some research areas there. However, I still felt that I did not know enough about some hot topics like big data.

The examples above are situations that could be viewed as some form of imposter syndrome.

Now, I would like to talk more about this.

Is the imposter syndrome something bad?

Yes, if it discourage you. No, if it motivates you to work harder and to improve yourself. Personally, when I perceive that I have some weaknesses, I will work harder to try to overcome them, and in the end, it will be positive. Thus, whether the imposter syndrome is something negative of positive depends on your attitude towards it.

How to overcome the imposter syndrome?

A good start is to recognize that you have several skills and to think about your strengths. Moreover, you should remember that although some other people may appear to be better at some things, you are better at other things. For example, another professor may seem to be better at teaching than you are but you may be a better researcher, or a student may seem better programmer than you, but you are better at writing research papers. And in any case, you can work out on your weaknesses to improve yourself.

Another important thing is to not be scared that people “unmask you” and discover that you are an “imposter“. Remember that no one is perfect and you should not be shy to admit htat you have weaknesses. You can then ask for help or questions to other people because this will help to improve yourself. For example, it is OK to ask a question about something that you do not understand during a research seminar.

Related to this, I will tell you another story. I remember some friend of mine that was scared of telling his supervisor that his programming skills were weak during his PhD studies. He did not tell his supervisor during his whole Ph.D but he was stressed that the supervisor may find out about it. In such case, I think that he should have been honest with the supervisor (and that is what I told him at that time). If he had done that, perhaps that the supervisor could have gave him some suggestions to improve his skills and my friend would have felt less stressful. But my friend found another solution. He instead worked hard and asked for help from many other students, and finally improved himself.

How long the imposter syndrome last?

There is no answer that is suitable for everyone. Some people overcome that syndrome by receiving some recognition from other people such as some award, a prize or obtaining a degree. But sometimes, the imposter syndrome stays there for a long time. For example, I have read some story about a tenured professor in a top level university that mentioned that he felt the imposter syndrome until he retired. After completing a paper, he was always thinking that he could maybe not find good ideas anymore for his next research projects.

Conclusion

In this blog post, I talked about the imposter syndrome and told you a few stories about it. The imposter syndrome is something very common at all levels from students to professors. The important is to know that you are not alone that you have strengths, and to think about this in a positive way to help you grow and improve yourself rather than discourage you. Don’t be afraid that people “unmask you” but instead ask questions, and work on improving yourself.

—
Philippe Fournier-Viger is a computer science professor and founder of the SPMF open-source data mining library, which offers more than 170 algorithms for analyzing data, implemented in Java.

Related posts:

Welcome!
How to publish in top conferences/journals? (Part 1) – The Blue Ocean Strategy
Unethical reviewers in academia
Posted in Academia, Research | Tagged , | 1 Comment

Big problem on my website on IONOS webhosting!

Posted on 2020-08-25 by Philippe Fournier-Viger

Hi all,

A bad news is that the database of this blog was reverted to 3 years ago due to some technical problem. I have used 1and1 IONOS as hosting service for my websites for the last 10 years, but now it seems that the database for the blog was overwritten with an old backup because everything is as it was 3 years ago in January 2017. How could it have happened?

I have contacted 1and1 IONOS to try to fix the issue, but they denied that it is their fault and did not have any backup older than 7 days. And my own backup is a little bit old… This is unfortunate. Thus, I think that maybe all blog posts of the last three years are lost (maybe 50+ posts). Anyway, this can of things happen, and I will continue the blog again soon…

But this time, I will not trust the 1and1 hosting service and do my own backups more often.

I am now trying to recover old posts through the Internet Wayback Machine and the cache of web search engines… I have recovered a dozen posts already and will continue but it may take some time.

Update: After several hours, I think that I have recovered most of the missing blog posts… but maybe there are some broken links. At least, most of the posts are not lost.

Philippe

Posted in Uncategorized | 9 Comments