ECML-PKDD 2016 Upcoming Submission Deadlines

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 http://www.ecmlpkdd2016.org/submission.html#call-demos.

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 results.

Additional information about the submission guidelines is available at http://www.ecmlpkdd2016.org/submission.html#call-nectar.