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 in all areas related to machine learning and knowledge discovery in databases and related application domains.
The goal of the Nectar Track is to offer conference attendees a compact overview of recent scientific advances at the frontier of machine learning and data mining, as published in related conferences and journals. We invite senior and junior researchers interested in Machine Learning and/or Knowledge Discovery in Databases, to submit summaries of their own work published in the neighboring fields, e.g. artificial intelligence, data analytics, bioinformatics, games, computational linguistics, 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 – and more.
Papers summarizing original and/or influential advances in machine learning and data mining are welcome; descriptions of new applications are welcome as well. Note that papers focusing on software implementations should rather be submitted to the demo track. Papers must be 4 pages and should be formatted according to the Author instructions and style files that can be found at http://www.springer.de/comp/lncs/authors.html
Papers should be submitted in the CMT submission system (select from the menu the Nectar track).
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.
Important dates: (all deadlines are at 23:59 of the mentioned date, Samoa Standard Time)
Submission deadline: Friday, June 14 Notifications: Friday, June 28 Submission of camera ready copies: July 8