Today, I will discuss what to do when a paper that you have submitted to a conference get rejected.
When submitting papers to a conference there are generally many papers that are submitted and get rejected. This is especially true for competitive conferences, where less than 1/4 of the papers get accepted, or sometimes even less than 1/10.
In the event where your paper get rejected, it is easy to take it personal and think that your research is not good or that you do not deserve to be published.It is also easy to blame the conference or the reviewers. However, a better attitude is to try to understand the reasons why your paper got rejected and then to think about what you can do to avoid the problems that lead to the rejection of your paper so that you can submit it somewhere else and that it can be accepted.
First, I often hear the complaint that a paper got rejected because the reviewers are not specialist and did not understand the paper. Well, it may be true. Sometimes, a paper get assigned to a reviewer that is not a specialist in your domain because you are not lucky or that a reviewer do not have enough time to read all the details of your paper. This can happen. But often the real reasons are:
- The paper was submitted to a conference that was too broadly related to the topic of the paper. For example, if you submit a paper about a data mining algorithm to a general computer science or artificial intelligence conference, it is possible that no data mining expert will read your paper. Choosing a conference is a strategic decision that should not be taken lightly when planning to submit a paper. A good way to choose a conference is to look at where papers similar to your topic have been published. This will give you a good idea about conferences that may be more “friendly” toward your research topic.
- Another possible reason is that your paper did not clearly highlight what is your contributions in the introduction. If the contributions of your paper are not clearly explained in the introduction, then the reviewer will have to guess what they are. From my experience, the top three parts that needs to be well-written in a paper are : (1) introduction, (2) experimental results and (3) conclusion. I have discussed with some top researchers and they have told me that they often first just look at these three parts. Then, if the paper looks original and good enough, they may also look at the method section of your paper. For this reason, introduction and conclusion should be very clear about what are your contributions.
- It is also possible that the reviewers did not understand why your research problem is interesting or challenging. In this case, it may also be a problem with the presentation. Your introduction should convince the reader that your research problem is important and challenging.
Second, another complaint that I often hear is that the reviewer did not understand something important about the technical details of your paper. Some reasons may be:
- It may be an issue with the presentation. Even if you are right that all the details were correctly presented in your paper, it is possible that the reviewer got bored reading the paper because of a poor presentation, or the lack of examples. Don’t forget that a very busy reviewer will not spend days reading your paper. Often a reviewer may just have a few hours to read it. In this case, rethinking the presentation of your paper to make it easier to read or more clear with respect to what the reviewer did not understand is a good idea.
- Another problem may be that the reviewer is not an expert in your field and that he may have some misconceptions about your field because he has not read much about it. For example, recently, a paper about itemset mining got rejected and the reviewer said something like “oh, this is just like the algorithm X from 20 years ago”. Well, this shows that the reviewer did not follow that field since a long time. To avoid this kind of bad reviews, a solution is to add some text to avoid the common misconceptions that a reviewer that is not specialist in your field may have. For example, recently, I was writing a paper about Itemset-trees, and I added a few lines to make it clear that this kind of trees are not the same as FP-Trees because many non-specialist will confuse them although there are very different because non-specialists usually only know the FP-Tree.
There are also some more serious reasons why a paper may be rejected. It may be that your paper is technically flawed, that your experiments are not convincing, that the data or results do not look good or original, that your method is not well explained or not compared with other relevant methods, that the paper is very badly written, etc. In these cases, the problem is more critical and it may be necessary to take the time to make a major improvement of your paper before submitting it. In this case, it may be better to take the time to seriously improve your paper instead of resubmitting it right away.
In any cases, if your paper is rejected, you probably already have spent a great deal of time on your paper and therefore it is generally a good idea to improve it and submit it somewhere else.
Lastly, I will give you a short story about one of my papers to give you hope if your paper got rejected. A few years ago, I submitted a paper to the conference Intelligent Tutoring Systems. It got rejected with bad reviews. Later, I almost submitted the same paper to EC-TEL, a good e-learning conference with an acceptance rate of about 1 /5. Then, the paper got accepted and it was even invited for a special issue of a good IEEE Transactions journal, and it was rated as one of the top 10 papers of the EC-TEL conference that year. So this is to tell you, that sometimes, it is possible to not get lucky and also that the choice of the conference may have a huge impact on if your paper get accepted or rejected. In my case, the same paper got a reject at ITS and was reviewers as one of the best papers at ECTEL, just by choosing a different conference.
So these are the advices that I wanted to write for today. Hope that you have enjoyed this post. If you like this blog, you can tweet about it and/or subscribe to my twitter account @philfv to get notified about new posts.
Philippe Fournier-Viger is a professor of Computer Science and also the founder of the open-source data mining software SPMF, offering more than 52 data mining algorithms.