Workshop on Knowledge Discovery, Data Mining and Machine Learning (KDML)

KDML is a workshop series that aims at bringing together the German Machine Learning and Data Mining community. The KDML 2017 Workshop is co-located with the annual LWDA 2017 – Learning, Knowledge, Data, and Analysis – conference and will take place

September 11th to 13th, 2017 at the University of Rostock, Rostock, Germany.

We invite submissions on all aspects of data mining, knowledge discovery, and machine learning. In addition to original research, we also invite reports on preliminary results and resubmissions of recently published articles. Moreover, KDML explicitly invites student submissions.

Topics of interest include but are not limited to

  • Foundations, models, and theory of machine learning and data mining
  • Supervised, semi-supervised, and unsupervised learning
  • Rule-based learning and pattern mining
  • Multiobjective learning
  • Deep learning
  • Temporal, spatial, and spatiotemporal data mining
  • Unstructured and semi-structured data mining
  • Network, graph, and Web mining
  • Text mining and mining
  • Distributed data mining
  • Data stream mining
  • Visual analytics
  • Big Data
  • Semantics in data mining and machine learning
  • Applications of data mining in all domains including social media digital libraries, bioinformatics, and finance
  • Open source frameworks and tools for data mining and machine learning

Types of Submissions

We solicit submissions under two different models:

  • full papers (up to 12 pages, peer-reviewed and to be published by LWDA)
  • presentations (a 1-page abstract , peer-reviewed and to be published by LWDA); these include, for instance, recent publications at top tier international venues, visionary ideas, work in progress, demonstration systems, industrial challenges, etc.

For both submission models, authors will have the opportunity to give a presentation at KDML. For the first model, accepted full papers will be published in the LWDA proceedings. For the second model, an extended abstract (one page) will be included in the LWDA proceedings.

Submissions are welcome in English and German. However, submissions in English are preferred. All papers have to be formatted according to the Springer LNCS guidelines and are to be submitted as PDF files to EasyChair. Please select the track Knowledge Discovery, Data Mining and Machine Learning.

At least two independent reviewers will review all submissions (under both models). The conference proceedings will be published as CEUR Workshop Proceedings and will be indexed by DBLP. All workshop participants have to register for the LWDA 2017 conference.

Important Dates

Submission deadline: June 19, 2017 July 3, 2017
Notification of acceptance: July 17, 2017 July 24, 2017
Camera-ready copy: August 14, 2017
LWDA 2017 Conference: September 11-13, 2017

Program Chairs

Prof. Dr. Ulf Brefeld, Leuphana Universität Lüneburg
Prof. Dr. Christian Bauckhage, Fraunhofer IAIS, St. Augustin

Program Committee

  • Dennis Becker, Leuphana Universität Lüneburg
  • Martin Becker, University of Würzburg
  • Vincent Bremer, Leuphana Universität Lüneburg
  • Eduardo Brito, Fraunhofer IAIS
  • Marwan Hassani, Eindhoven University of Technology
  • Alexander Hinneburg, Martin-Luther-University Halle-Wittenberg
  • Andreas Hotho, University of Würzburg
  • Kristian Kersting, TU Darmstadt University
  • Ralf Krestel, Hasso Plattner Institute
  • Florian Lemmerich, Gesis - Leibniz Institute for the Social Sciences, Cologne
  • Ulf Leser, Humboldt-Universität zu Berlin
  • Sebastian Mair, Leuphana Universität Lüneburg
  • Christoph Martin, Leuphana Universität Lüneburg
  • Emmanuel Müller, Hasso Plattner Institute
  • Nico Piatkowski, TU Dortmund University
  • Ute Schmid, University of Bamberg
  • Rafet Sifa, Fraunhofer IAIS
  • Maryam Tavakol, Leuphana Universität Lüneburg