Monday, July 13

How to Improve your chances of getting your paper accepted (at least at KDD)

Eamonn Keogh a professor at UC Riverside gave a tutorial at KDD 2009 titled: How to do good research, get it published in SIGKDD and get it cited!. Thanks to William Webber for his summary and pointing this out to me.

The slides from the tutorial are now available online. While it was given at KDD, many of the same principles described apply to other conferences like CIKM, SIGIR, etc...

Here are a few steps that he outlines to make your paper more likely to get accepted:
  • Anchoring. Anchor your readers on the first page. This means a solid and captivating title, abstract, and introduction. Motivate your paper clearly.

  • Reproducibility. Make your experiment reproducible by telling your readers what you did and how you did it: parameters, algorithms, data pre-processing, etc... One of most common causes of unreproducible results is complexity and parameters: be explicit and try not use algorithms whose parameters someone else won't be able to understand or replicate.

  • Unjustified choices are bad. Given an explanation for every choice you made, even if it was arbitrary.

  • Choose your words carefully. Words can be confusing: optimal, proved, significant, theoretically. Be sure to define any abbreviations early!

  • Use all your space. Don't leave empty space in your paper. Use it to be show more results or give more detail.

  • Use Figures Effectively. Make good figures that clearly illustrate your point. (see the paper for examples of good and bad figures)

Read the tutorial for the Top Ten Reasons Your Paper Got Rejected. Here are a few highlights:
  1. The paper is out of scope for the conference.
  2. Not an interesting or important problem
  3. Sloppy paper: typos, unclear figures, and poor writing
  4. The experiments are not reproducible
  5. There was an easier way to do solve the problem and you did not compare against it.
I'll add: the results are not compelling. You tried lots of things and nothing worked, or you managed only a very tiny improvement over the baseline. Negative results are important, but good results are more likely to be published. This is because if your techniques don't produce results then you have to explain, in detail, why they didn't work. This takes a lot of time and effort to do thoroughly and most people don't do it well.

See also the Research Methods class taught by David Jensen here at UMass. You can see the schedule from this Spring's class.

1 comment:

  1. Simon Peyton-Jones also has a great site with this kind of advice:

    Is it just me, or is cut-and-paste broken in these comments on the latest Firefox?