Key Dates and Deadlines

Given the special nature of the journal track submitted papers have to adhere to the following eligibility criteria:

• Papers have to satisfy the high-quality criteria of journal papers and at the same time lend themselves to conference talks.
• Journal versions of previously published conference papers and survey papers will not be considered for the special issue.
• A paper rejected by the Machine Learning Journal should not be submitted to the Data Mining and Knowledge Discovery Journal and vice versa.
• Papers that do not fall into the eligible category may be rejected without formal reviews but can, of course, be resubmitted as regular papers to the Springer journals.

Authors are encouraged to adhere to the best practices of Reproducible Research (RR), by making available data and software tools for reproducing the results reported in their papers. For the sake of persistence and proper authorship attribution, we require the use of standard repository hosting services, e.g. dataverse, mldata, openml, mloss, bitbucket, github for source code.

The journal track allows continuous submissions till December 2023. Papers will be processed and set out for review after the following cutoff date:

Submission deadline: 2023-12-05

The deadline on each of these dates is 23:59, Anywhere on Earth (AoE). We strive for a high quality and efficient review process. For each submission, we aim at obtaining three reviews from experienced reviewers, including members of the Guest Editorial Board. Our goal is to arrive at an initial decision about 10 weeks after each cutoff date, though meeting this target may not always be possible. After the initial review phase, many papers will require substantial revisions, and the revised paper will be re-reviewed, which extends the review process. Consequently, a paper’s chance of finishing the review cycle and being included in the ECML PKDD 2024 special issue decreases with each subsequent cutoff date. This means that accepted papers, especially those that were submitted to the later deadlines, may be included in the ECML PKDD 2025 (or even later) special issue (and subject to approval of the ECML PKDD steering committee and future organizers). The reviewing process is single-blind.

To submit to this track, authors have to make a journal submission CMT site as well as the journal system

• Authors have to submit their paper to the CMT submission site: CMT submission site by submitting the title, abstract, adding the author names, choosing the related to the paper areas, and indicating which of the two journals the paper is intended to.
• The full paper has to be submitted to the journal system of the selected journal:
  • The Springer Data Mining and Knowledge Discovery journal (submission site) or
  • The Springer Machine Learning journal (submission site, no paper can be submitted to both).

Templates can be found at here. It is highly recommended that submitted papers do not exceed 20 pages including references. Every paper may be accompanied with unlimited appendices.

• What is the main claim of the paper? Why is this an important contribution to the machine learning/data mining research area.
• What is the evidence provided to support claims? Be precise.
• Report 3-5 most closely related contributions in the past 7 years (authored by researchers outside the authors’ research group) and briefly state the relation of the submission to them.
• Specify 5 general keywords and five specific keywords describing the main research activity presented in the manuscript.
• Declare any conflict of interest by reporting the email domains of all institutions with which the authors have an institutional conflict of interest. Authors have an institutional conflict of interest if they are currently employed or have been employed at this institution in the past three years, or if the authors have extensively collaborated with this institution within the past three years. Authors are also required to identify all Guest editorial Board Members with whom the authors have a conflict of interest. Examples of conflicts of interest include co-authorship in the last five years, a colleague in the same institution within the last three years, and advisor/student relationships.

Who are the most appropriate reviewers for the paper? Authors are required to suggest up to four candidate reviewers (especially if external to the Guest Editorial Board), including a brief motivation for each suggestion. Optionally, list up to four researchers/potential reviewers with competing interests that should not be considered for reviewers.

• There is bidding, which will start after Dec 5.