The journal track has closed on March 3 and only revisions to previously submitted papers will be considered. The proceedings track has closed on April 22 (except for light revisions of journal submissions, see below).
Regular contributions are to be submitted using the CMT conference management tool. Papers should be in LNCS format and have at most 16 pages. Reviewing will be single-blind. The formatting guidelines of Springer Verlag for the LNCS series apply, and the author instructions and style files must be used.
Revised versions of manuscripts previously submitted to the journal track should be submitted to the resubmission track in the CMT system, rather than the main track. The authors of such resubmissions are also requested to upload a file with responses to the original reviews as supplementary material, after uploading the revised manuscript. If the notification for the previous journal submission explicitly mentioned that only light re-review would be needed, then the revised version may be submitted until May 24, rather than April 22.
Journal Track (closed)
The submission and notification process will be handled via the editorial manager system of the Springer journals. As the corresponding author, you make a choice to either submit to the Machine Learning journal, or to the Data Mining and Knowledge Discovery journal.
The submission system for Data Mining and Knowledge Discovery can be found on:
The submission system for Machine Learning can be found on:
In both cases, an article is submitted to the journal track by choosing ‘ECMLPKDD 2013′ as the article type.
Articles must adhere to all requirements of the respective journals. See the call for papers for additional requirements and recommendations relevant to the journal track.
Articles should be at most 20 pages long. Submissions exceeding this length will not be given priority during reviewing and may, as a consequence, be under review for a longer period.
The cover letter (for Data Mining and Knowledge Discovery) or contribution information sheet (for Machine Learning) must explicitly address the following questions:
- What is the main claim of this paper? Why is it an important contribution to machine learning and/or data mining?
- What is the evidence you provide to support your claim?
- What papers by other authors make the most closely related contributions, and how does your paper relate to those?
- Have you published parts of this paper before? If yes, give details and describe how your paper provides a significant contribution beyond the previous paper(s).
- Has (a previous version of) this paper been submitted before? If yes, where was the most recent previous version submitted? What was the main criticism of the reviewers? How has it been addressed in this version?
The cover letter or contribution information sheet must also include the following statement: “If the paper is accepted, it will be presented at the ECMLPKDD 2013 conference by one of the authors.”
Submissions to the ECMLPKDD 2013 journal track will be processed differently than other articles submitted to these journals. In particular, the abstracts and titles of the submitted articles will be sent to all members of a guest editorial board (GEB), which will be asked to bid on these articles. You may wish to take this into account when writing your abstract.
We strive for notification within 8 weeks although we cannot guarantee this. In particular, for submissions in unusually busy batches, such as (likely) the last one, a delay can be expected. On 12/12/2012, the mean time from submission to notification, for fully reviewed papers, was 59 days.
More information about the journal track can be found here.