[DL] ECML-PKDD 2016 Joint Call for Papers

Olana Missura olanochka at gmail.com
Thu Jan 21 01:34:32 CET 2016

ECMLPKDD 2016 Joint Call for Papers

Riva Del Garda, Italy, September 19-23

Apart from the main conference track the ECMLPKDD conference offers a
variety of other tracks tailored to specific interests, such as


   Journal Track


   Nectar Track

   Industrial Track

   PhD Forum

For a short summary of each and their important dates, read below. Detailed
information about all tracks and submission procedures is available at

Note: All deadlines are at 23:59 CET (Central European Time).
Journal Track

The 2016 cut-off dates for the bi-weekly batches are: Jan 31, Feb 14, Feb
28, Mar 13, Mar 27.

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.

Additional information about the submission guidelines is available at
Demos Track


   Demo submission deadline: Friday, May 13, 2016

   Notification of acceptance: Monday, June 20, 2016

   Camera-ready paper due: Friday, July 1, 2016

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. A commercial software
is 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
Artificial Intelligence" (LNAI) 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.

Additional information about the submission guidelines is available at
Nectar Track


   Submission deadline: Friday, May 13, 2016

   Notifications of acceptance: Monday, June 20, 2016

   Submission of camera ready copies: Friday, July 1, 2016

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. We invite senior and junior researchers
to submit summaries of their own work published in neighbouring fields,
such as (but not limited to) artificial intelligence, data analytics,
bioinformatics, games, computational linguistics, natural language
processing, computer vision, 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 summarises 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

Additional information about the submission guidelines is available at
PhD Forum


   Paper submission: Wednesday, June 15, 2016

   Author notification: Friday, July 15, 2016

   Camera-ready: Friday, August 5, 2016

   PhD Forum: Monday, September 19, 2016 (tentative)

The European Conference on Machine Learning and Principles and Practice of
Knowledge Discovery in Databases (ECMLPKDD) includes a PhD Forum on machine
learning and knowledge discovery. The purpose of this forum is to provide
an environment specifically for junior PhD students to exchange ideas and
experiences with peers in an interactive atmosphere and to get constructive
feedback from senior researchers in data mining, machine learning, and
related areas. The focus of the discussion at the PhD Forum would be the
work in progress of junior PhD students, with 1-3 years of research
experience, towards their dissertation.

The PhD Forum is open to two types of submissions: work-in-progress papers and
PhD project plans. Detailed information about the submission guidelines is
available at http://www.ecmlpkdd2016.org/submission.html#CallPhD.
Industrial Track


   Abstract submission deadline: Friday, April 15, 2016

   Paper submission deadline: Wednesday, April 20, 2016

   Author notification: Monday, June 20, 2016

   Camera-ready: Friday, July 1, 2016

   Industrial track presentations: Friday, September 23, 2016

The INDUSTRIAL, GOVERNMENTAL & NGO Track of ECMLPKDD 2016 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 links between
those engaged in scientific research and practitioners working to improve
big data mining and large scale machine learning analytics. Novel ideas,
controversial issues, open problems and comparisons of competing approaches
are strongly encouraged. Experiences from practitioners provide crucial
input into future research directions and allow others to learn from
successes and failures.

Submissions are invited on innovative real-world data systems and
applications, state-of-the-art practices, surveys from real-world projects
and industrial experiences, and identification of unsolved research
challenges of machine learning, knowledge discovery and data mining.  The
 INDUSTRIAL, GOVERNMENTAL & NGO 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 Science”, or

Detailed information about the submission guidelines is available at
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