ECML-PKDD 2017 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD)

European Conference on Machine Learning and Principles and Practice of
Knowledge Discovery in Databases (ECML-PKDD)
Skopje, Macedonia, September 18-22, 2017 (http://www.ecmlpkdd2017.org).
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Submissions are solicited for the 2017 edition of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017). The conference provides an international forum for the discussion of the latest high-quality research results in all areas related to machine learning and knowledge discovery in databases and other innovative application domains. The 2017 conference will take place in Skopje, Macedonia, 18‐22 September 2017.
Submissions are invited on all aspects of machine learning, knowledge discovery and data mining, including real-world applications. Following the tradition of ECML-PKDD, we expect high-quality papers in terms of their scientific contribution, rigor, correctness, quality of presentation and reproducibility of experiments.
Submission process
Electronic submissions will be handled via CMT at the following address: https://cmt.research.microsoft.com/ECMLPKDD2017/. Please note that user accounts in each CMT conference are independent of other conferences, so you will need to create a new account. Abstracts need to be registered by Thursday April 13, 2017 and full submissions will be accepted until Thursday April 20, 2017. Papers must be written in English and formatted according to the Springer LNAI guidelines. Author instructions, style files and copyright form can be downloaded at: http://www.springer.de/comp/lncs/authors.html. The maximum length of papers is 16 pages in this format. Overlength papers will be rejected without review (papers with smaller page margins and font sizes than specified in the author instructions and set in the style files will also be treated as overlength).
Up to 10 MB of additional materials (e.g. proofs, audio, images, video, data or source code) can be attached to the submission. Note that the reviewers and the program committee reserve the right to judge the paper solely on the basis of the 16 pages of the paper; looking at any additional material is up to the discretion of the reviewers and is not required.
Reviewing process
The review process is single-blind (authors identities known to reviewers). Submissions will be evaluated on the basis of technical quality, novelty, potential impact, and clarity. Authors will have the opportunity to point out factual errors, obvious mistakes, or misconceptions by reviewers during a rebuttal phase following the release of initial reviews.
Dual submissions policy
Papers submitted should report original work. ECML-PKDD 2017 will not accept any paper that, at the time of submission, is under review or has already been accepted for publication in a journal or another conference. Authors are also expected not to submit their papers elsewhere during the review period. The dual submissions policy applies during the whole ECML-PKDD 2017 reviewing period from April 20 to June 22, 2017.
Reproducible research 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. Authors may flag their submissions as RR and make software and data accessible to reviewers and to the program committee who will verify the accessibility of software and data. Links to data and code will then be inserted in the final version of RR papers. For the sake of persistence and proper authorship attribution, we require the use of standard repository hosting services such as Dataverse, mldata.org, OpenML, etc. for data sets, and mloss.org, Bitbucket, GitHub, etc. for source code. If data or code gets updated after the paper is published, it is important to enable researchers to access the versions that were used to produce the results reported in the paper.