ECML-PKDD Journal Track 2017 : Journal track of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2017
Call For Papers
CALL FOR PAPERS
Journal track of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 2017
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 (ECML-PKDD) 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.
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 ECML-PKDD issues of the journals commit themselves to present their results at the ECML-PKDD 2017 conference in case of acceptance.
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.
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 ECML-PKDD 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.
You can contact the Journal Track Chairs at email@example.com
Nikola Simidjievski & Dragi Kocev
Publicity Chairs of ECML-PKDD 2017