Journal track submission for ECML-PKDD 2017 is *OPEN*

[ECML-PKDD 2017]

CALL FOR PAPERS

Journal track of the European Conference on Machine Learning and Principles
and Practice of Knowledge Discovery in Databases (ECMLPKDD) 2017

www.ecmlpkdd2017.org

September 18-22, 2017, Skopje, Macedonia



We invite submissions for the journal track of the European Conference on
Machine Learning and Principles and Practice of Knowledge Discovery in
Databases (ECMLPKDD) 2017. 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.
This implies that 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 http://dataverse.org, http://mldata.org,
http://openml.org, etc. for data sets, and http://mloss.org,
https://bitbucket.org, https://github.com, etc. for source code. Authors
who submit their work to the special ECMLPKDD issues of the journals commit
themselves to present their results at the ECMLPKDD 2017 conference in case
of acceptance.

Reviewing process:
The journal track allows continuous submissions from the end of July 2016
to the end of March 2017. We start with a single cutoff per month,
increasing to two cutoffs per month starting October 2016 on which we
distribute papers to reviewers. More precisely, we will have the following
cut-off dates:
- 31.7.2016, 28.8.2016, 25.9.2016
- 9.10.2016, 23.10.2016, 6.11.2016, 20.11.2016, 4.12.2016, 18.12.2016
- 8.1.2017, 22.1.2017, 5.2.2017, 19.2.2017, 5.3.2017, 19.3.2017

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. We aim to send the first decision letters 5-7 weeks
from submission. This suggests that we should be able to consider all of
the submissions for the special issue. However, the experience from the
past editions of the journal track shows that often there is a need for
revisions of the submissions and this extends the review process.
Considering this, for submissions for the 5.2.2017 cut-off date and later,
the chance of inclusion in the ECML PKDD 2017 special issue exponentially
decreases and, consequently, will not make it on time for presentation at
the 2017 conference. Furthermore, submissions after this cut-off date will
not adhere to the fast track reviewing procedure but we will employ the
review timeline for a normal journal submission (because the reviewing
period for the main conference will overlap with these review cycles).
Moreover, the 2015 JT chairs recorded a decreasing acceptance rate for
submissions after mid-February. Finally, 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 2017 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. For submissions to
both journals, authors are required to include an information sheet (up to
2 pages) that contains a short summary of their contribution and
specifically address the following questions:
1. What is the main claim of the paper? Why is this an important
contribution to the machine learning/data mining literature?
2. What is the evidence provided to support claims? Be precise.
3. 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.
4. Who are the most appropriate reviewers for the paper? Authors are
encouraged to suggest up to four candidate reviewers (especially if
external to the Guest Editorial Board), including a brief motivation for
each suggestion.
5. Optionally, list up to four researchers/potential reviewers with
competing interests that should not be considered for reviewers.

Contact:
You can contact the Journal Track Chairs at jt_chairs at ecmlpkdd2017.org

Best Regards,

Nikola Simidjievski & Dragi Kocev

Publicity Chairs of ECML-PKDD 2017
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