Call for papers - ECMLPKDD 2018 Journal Track

[jt_chairs at ecmlpkdd2018.org]

[Apologies for cross-posting]

*ECML/PKDD 2018 Journal Track*

We invite submissions for the journal track of the European Conference 
on Machine Learning and Principles and Practice of Knowledge Discovery 
in Databases (ECMLPKDD) 2018. The journal track of the conference is 
implemented in partnership with the Machine Learning Journal and the 
Data Mining and Knowledge Discovery Journal. The conference provides an 
international forum for the discussion of the latest high-quality 
research results in all areas related to machine learning, data mining, 
and knowledge discovery.

*Eligibility criteria*

Papers on all topics related to machine learning, knowledge discovery, 
and data mining are invited. However, given the special nature of the 
journal track, only papers that satisfy the quality criteria of journal 
papers and at the same time lend themselves to conference talks will be 
considered. Consequently, journal versions of previously published 
conference papers, or survey papers will not be considered for the 
special issue. Papers that do not fall into the eligible category may be 
rejected without formal reviews but can of course be resubmitted as 
regular papers.
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 such as dataverse, mldata, openml, 
etc. for data sets, and mloss, bitbucket, github, etc. for source code.
Authors who submit their work to the ECMLPKDD special issues of these 
journals commit themselves to present their paper at the ECMLPKDD 2018 
conference if it is accepted.

*Reviewing process*

The journal track allows continuous submissions from the end of August 
2017 to the end of January 2018.
Papers will be processed and sent out for review after each of the 
following five cutoff dates:

  * August 27th, 2017
  * October 1st, 2017
  * November 5th, 2017
  * December 10th, 2017
  * January 28th, 2018

The deadline on each of these dates is midnight, Central European Time.
We strive for a high quality and efficient review process. Each 
submission will be evaluated by three experienced reviewers including 
members of the Guest Editorial Board. Our goal is to arrive at an 
initial decision about 8 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 rereviewed, which extends the review process. Consequently, a 
paper’s chance of finishing the review cycle and being included in the 
ECMLPKDD 2018 special issue decreases with each subsequent cutoff date. 
Inclusion of the delayed papers in forthcoming special issues and 
conference editions is subject to approval of the respective
Program and Journal track chairs.

*Submission procedure*

To submit to this track, authors have to make a journal submission to 
either the Springer Data Mining and Knowledge Discovery journal or the 
Springer Machine Learning journal, and select the type of submission to 
be for the ECMLPKDD 2018 special issue. It is recommended that submitted 
papers do not exceed 20 pages including references and appendices, 
formatted in the Springer journal style (svjour3, smallcondensed). This 
is a soft limit, but if a submission exceeds the limit, please provide a 
brief justification regarding the length in the cover letter. Arriving 
at an initial decisions for papers over 20 pages may take longer.

Both journals require authors to include an information sheet (for 
Machine learning submissions) or a cover letter (up to 2 pages) as a 
supplementary material (for Data Mining and Knowledge Discovery 
submissions) that contains a short summary of their contribution and 
specifically address the following questions:

  * What is the main claim of the paper? Why is this an important
    contribution to the machine learning/data mining literature?
  * 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.
  * 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.


*To submit to the journals, please go to:*
Submit to Machine Learning
https://www.editorialmanager.com/mach

Submit to Data Mining and Knowledge Discovery
https://www.editorialmanager.com/dami

*Contact*
You can contact the Journal Track Chairs: jt_chairs at ecmlpkdd2018.org
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