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, 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 ECML-PKDD 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 are papers that summarizes a line of work that comprises older and more recent papers. The described work should be relevant to a broad audience within ECML-PKDD, 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 ECML-PKDD rather than the Nectar Track.
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. Similarly to last year’s conference, the proceedings will be published after the conference and will include only the papers for which authors have presented at the conference. During the conference, a camera-ready version of the papers will be available for conference participants.
- Submission deadline: Thursday, May 10, 2018
- Notification of acceptance: Thursday, June 14, 2018
- Submission of camera ready copies: Friday, June, 29, 2018
All deadlines expire on 23:59 (AOE)
In case you have any question, please do not hesitate to contact the Nectar Track Chairs, Ulf Brefeld and Fabio Pinelli at firstname.lastname@example.org