############################################################ 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). ############################################################ 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 neighbouring 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 http://www.springer.de/comp/lncs/authors.html. 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 CMT submission system <https://cmt.research.microsoft.com/ECMLPKDD2017/> (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* · Notifications of acceptance: *Thursday, June 22, 2017* · Submission of camera ready copies: *Thursday, July 6, 2017* Contacts In case you have any question, please do not hesitate to contact the Nectar Track Chairs (Donato Malerba, Jerzy Stefanowski) at nectar_cha...@ecmlpkdd2017.org. We are looking forward to your proposals. -- Nikola Simidjievski & Dragi Kocev Publicity Chairs of ECML-PKDD 2017
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