Conf/CfP - Machine Learning and Principles and Practice of Knowledge Discovery in Database, 18‐22 September 2017, Skopje, Macedonia

Publish Date: Mar 09, 2017

Deadline: Apr 13, 2017

The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery will take place in Skopje, Macedonia, September 18–22, 2017.

This event is the premier European machine learning and data mining conference and builds upon a very successful series of 27 ECML and 20 PKDD conferences, which have been jointly organized for the past 15 years.

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) 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 dataverse, mldata, openml, etc. for data sets, and mloss, bitbucket, github, 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 6-8 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. 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 (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.

Contact

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

Conference Track

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, rigour, correctness, quality of presentation and reproducibility of experiments.

Submission process

Electronic submissions will be handled via Microsoft CMT. 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 LNCS guidelines.

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.

Authors who submit their work to ECML-PKDD commit themselves to present their paper at the ECML-PKDD 2017 conference in case of acceptance. Additionally, ECML-PKDD considers the author list submitted with the paper as final. No additions or deletions to this list may be made after paper submission, either during the review period, or in case of acceptance, at the final camera ready stage.

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 date of April 26th 2017 (we have a 5-days withdrawal period), 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 following period: from April 26 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 who will verify the accessibility of software and data. Links to data and code must 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, figshare, Zenodo, etc. for data sets, and mloss.org, Bitbucket, GitHub, figshare (where it is possible to assign a DOI) 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. Authors who do not have a preferred repository should consult Springer Nature’s list of repositories and research data policy (we adopt type 2).

Proceedings

The conference proceedings will be published by Springer in the Lecture Notes in Computer Science series (LNCS). This year, the proceedings will be published after the conference and will include only the papers that authors have presented at the conference. During the conference, a camera-ready version of the papers will be available for conference participants.

In addition to normal conference submissions, papers can be submitted to other tracks: Industrial, Governmental and NGO; Demo; Ph.D.; Nectar; journal track. Accepted papers in all the tracks, including journal track, will be presented at the conference.

For information about other tracks, please see the separate call for papers.

Important dates

  • Abstract submission deadline: Thursday April 13, 2017
  • Paper submission deadline: Thursday April 20, 2017
  • Author notification: Thursday June 22, 2017
  • Camera ready submission: Thursday July 6, 2017

Contact

For any additional questions you can contact the Program Chairs (Michelangelo Ceci, Jaakko Hollmén, Ljupčo Todorovski, Celine Vens) at pc_chairs@ecmlpkdd2017.org

Demo Track

We solicit submissions for demos for ECML PKDD 2017 in Skopje, Macedonia. Submissions must describe working systems and be based on state-of-the-art machine learning and data mining technology. These systems may be innovative prototype implementations or mature systems that use machine learning techniques and knowledge discovery processes in a real setting. Systems that use basic statistics are not acceptable. Commercial software systems are not acceptable.

The accepted papers for demos will be included in the conference proceedings, to be published by Springer Verlag in the "Lecture Notes in Computer Science" (LNCS) Series. The demos will be presented in a special demonstration session. At least one of the demo submitters must register for the conference, and perform the demo on site.

Submission Guidelines

All aspects of the submission and notification process will be handled online via the conference Microsoft CMT submission site. Please choose the right track during the submission. Instructions concerning the submission (except for the "reproducible research" part which is not relevant for a demo paper), camera-ready formatting and copyright transfer for conference papers also hold for demo papers, unless otherwise specified.

A demonstration submission must be up to 4 pages long. It must provide adequate information on the system's components and the way the system is operated, including e.g. screenshots. Submitters should keep in mind that the description of a demo has inherently different content than a research paper submitted to the main conference. A successful demonstration paper provides satisfactory answers to the following questions:

  • What are the innovative aspects or in what way/area does it represent the state of the art?
  • Who are the target users and why is the system interesting/useful for them?
  • If there are similar/related pieces of software, what are the advantages and disadvantages of the presented one?

Important dates

  • Demo submission deadline: Thursday, May 11, 2017
  • Notification of acceptance: Thursday, June 22, 2017
  • Camera-ready paper due: Thursday, July, 6, 2017
  • Presentation of the live demos: Tuesday, September 19 and Thursday, September 21, 2017

Contact

For further information please contact the Demo Track Chairs (Marinka Zitnik, Jesse Read) at demo_chairs@ecmlpkdd2017.org

Nectar Track

The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD) 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 related application domains.

The goal of the Nectar Track, started in 2012, is to offer conference attendees a compact overview of recent scientific advances at the frontier of machine learning and data mining with other disciplines, as published in related conferences and journals. For researchers from the other disciplines, the Nectar Track offers a place to present their work to the ECMLPKDD community and to raise the community's awareness of data analysis results and open problems in their field. We invite senior and junior researchers to submit summaries of their own work published in neighboring fields, such as (but not limited to) artificial intelligence, big data analytics, bioinformatics, cyber security, games, computational linguistics, natural language processing, information retrieval, computer vision and image analysis, geoinformatics, health informatics, database theory, human computer interaction, information and knowledge management, robotics, pattern recognition, statistics, social network analysis, theoretical computer science, uncertainty in AI, network science, complex systems science, and computationally oriented sociology, economy and biology, as well as critical data science/studies.

Particularly welcome is work that summarizes a line of work that comprises older and more recent papers. The described work should be relevant to a broad audience within ECMLPKDD, and (a) illustrate the pervasiveness of data-driven exploration and modelling in science, technology, and the public, as well as innovative applications, and/or (b) focus on theoretical results.

Note that papers focusing only on software implementations rather than on the interdisciplinary use of ML/DM should rather be submitted to the demo track. Work at the core of ML/DM should target the main tracks of ECMLPKDD rather than the Nectar Track.

Submission Guidelines

Papers must be 4 pages and should be formatted according to the Author instructions, style files and copyright form that can be found at "Lecture Notes in Computer Science" (LNCS) Series.

Submissions must clearly indicate which corresponding original publication(s) are presented, and must clearly motivate the relevance of the work in the context of machine learning and data mining. Papers should be submitted through the conference Microsoft CMT submission site (select from the menu the Nectar track). Accepted Nectar contributions will be presented as oral presentations and included in the conference proceedings.

Important dates

  • Submission deadline: Thursday, May 18, 2017
  • Notification of acceptance: Thursday, June 22, 2017
  • Submission of camera ready copies: Thursday, July, 6, 2017

Contact

In case you have any question, please do not hesitate to contact the Nectar Track Chairs (Donato Malerba, Jerzy Stefanowski) at nectar_chairs@ecmlpkdd2017.org.

Applied Data Science Track

The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD, provides an international forum for the discussion of the latest high-quality research results and applications in all areas related to machine learning, data mining and knowledge discovery in databases, as well as other innovative application domains. The 2017 edition of ECML-PKDD will take place in Skopje, Macedonia, September 18-22.

The Applied Data Science Track of ECML-PKDD 2017 follows the success of the previous years with a separate Program Committee and a separate Proceedings volume. The track aims to bring together participants from academia, industry, governments and NGOs (non-governmental organizations) in a venue that highlights practical and real-world studies of machine learning, knowledge discovery and data mining. This track wants to encourage mutually beneficial interactions between those engaged in scientific research and practitioners working to improve big data mining and large-scale machine learning analytics. Novel and practical ideas, open problems in Applied Data Science, description of application–specific challenges and unique solutions adopted in bridging the gap between research and practice are some of the relevant topics for this track.

Submissions are invited on innovative real-world data systems and applications, state-of-the-art practices, identification of unsolved challenges in deploying research ideas in practical data science applications, surveys from real-world projects and industrial experiences that advance the understanding of the contributions and limitations of machine learning and data mining technologies in real-world applications.

The Applied Data Science Track is distinct from the Research Track in that submissions solve real-world problems and focus on applications and challenges. Submissions must clearly identify one of the following three areas they fall into: "Engineering Systems", "Data Analytics", or "Challenges".

The criteria for submissions are the following:

  • Engineering Systems: presents non-trivial systems or infrastructure designed to solve real-world big data problems, where the main novelty is the approach to design, deploy and manage the system.
  • Data Analytics: presents new practical data science studies that provide value to the community of practitioners, and researchers in industry, governments and NGOs. These studies should be useful, non-trivial, and externally validated.
  • Challenges: presents novel ideas, current data analytic challenges, controversial issues, open problems and comparisons of competing approaches.

Proceedings

The Applied Data Science Track proceedings of ECML-PKDD 2017 will be published by Springer in a separate volume of the Proceedings of ECML-PKDD 2017, in the "Lecture Notes in Computer Science" (LNCS) Series. At least one of the authors of each accepted paper must register for the conference to present the paper on site.

Submissions

The papers must be written in English and formatted according to the Springer LNCS guidelines. Author's instructions and style files can be downloaded at LNCS.

The maximum length of papers is 12 pages in this format. Longer 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 over length). Papers submitted should report original work; ECML-PKDD 2017 will not accept any paper, which, 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.

To submit a paper:

  • Create an account and log into the conference CMT submission site for ECML-PKDD 2017. Please note that user accounts for different CMT conferences are independent of each other. Thus, any credentials you might have for previous CMT conferences will not work for ECML-PKDD 2017.
  • Specify your conflict domains.
  • Create a New Paper submission.
  • Select the Applied Data Science Track.
  • Complete the submission form by providing title, authors, one primary subject area, any number of secondary subject areas and a short abstract. The manuscript must be uploaded in pdf format. You will also need to answer the questions at the site.

Evaluation and Decision Criteria

Submissions will be evaluated on the basis of relevance, novelty, originality, technical soundness, clarity, empirical and/or practical validation, external significance and validity, quality and consistency of presentation, and appropriate comparison to related work. Special emphasis will be placed on the relevance of the proposed contribution to practitioners. Authors are strongly encouraged to make data and code publicly available whenever possible.

Authors of papers submitted to the Applied Data Science Track of ECML-PKDD 2017 must identify the application domain that is the subject of their paper. Application domains include, but are not limited to the following: finance, government, e-commerce, retail, mobile, medicine, healthcare, security, public policy, science, engineering, law, manufacturing, and communications.

Evaluation and Decision Criteria

The Applied Data Science Track of ECML-PKDD 2017 has a separate Program Committee from the Research Track. Papers submitted to the Applied Data Science Track of ECML-PKDD 2017 will be reviewed by at least three referees. The review process is single-blind (reviewer identities unknown to authors) and there will be no opportunity for author rebuttal. This decision was made to minimize reviewer workload and to concentrate it in time, which may ultimately result in better quality reviews and decisions. If necessary, a discussion will take place among the reviewers of a paper until a decision is reached.

Important dates

  • Abstract submission deadline: Thursday, April 13, 2017
  • Paper submission deadline: Thursday, April 20, 2017
  • Author notification: Thursday, June 22, 2017
  • Camera ready submission: Thursday, July, 6, 2017

Contact

In case you have any question, please do not hesitate to contact the Applied Data Science Track Chairs (Yasemin Altun, Kamalika Das and Taneli Mielikäinen) at industrial_chairs@ecmlpkdd2017.org.

For more information please click "Further Official Information" below.


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