Table Of ContentBettina Berendt · Björn Bringmann
Élisa Fromont · Gemma Garriga
Pauli Miettinen · Nikolaj Tatti
Volker Tresp (Eds.)
Machine Learning and
3
Knowledge Discovery
5
8
9
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A in Databases
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European Conference, ECML PKDD 2016
Riva del Garda, Italy, September 19–23, 2016
Proceedings, Part III
123
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Lecture Notes in Arti cial Intelligence 9853
Subseries of Lecture Notes in Computer Science
LNAI Series Editors
Randy Goebel
University of Alberta, Edmonton, Canada
Yuzuru Tanaka
Hokkaido University, Sapporo, Japan
Wolfgang Wahlster
DFKI and Saarland University, Saarbrücken, Germany
LNAI Founding Series Editor
Joerg Siekmann
DFKI and Saarland University, Saarbrücken, Germany
More information about this series at http://www.springer.com/series/1244
ö
Bettina Berendt Bj rn Bringmann
(cid:129)
É
lisa Fromont Gemma Garriga
(cid:129)
Pauli Miettinen Nikolaj Tatti
(cid:129)
Volker Tresp (Eds.)
Machine Learning and
Knowledge Discovery
in Databases
European Conference, ECML PKDD 2016
–
Riva del Garda, Italy, September 19 23, 2016
Proceedings, Part III
123
Editors
Bettina Berendt Pauli Miettinen
Department ofComputer Science MaxPlanckInstitute for Informatics
KULeuven Saarbrücken
Leuven Germany
Belgium
Nikolaj Tatti
Björn Bringmann AaltoUniversity School of Science
Deloitte GmbH Espoo
Munich Finland
Germany
Volker Tresp
ÉlisaFromont Siemens AGandLudwig Maximilians
Laboratoire HubertCurien University of Munich
JeanMonnet University Munich
Saint-Etienne Germany
France
Gemma Garriga
Allianz SE
Munich
Germany
ISSN 0302-9743 ISSN 1611-3349 (electronic)
Lecture Notesin Artificial Intelligence
ISBN 978-3-319-46130-4 ISBN978-3-319-46131-1 (eBook)
DOI 10.1007/978-3-319-46131-1
LibraryofCongressControlNumber:2016950748
LNCSSublibrary:SL7–ArtificialIntelligence
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Foreword to the ECML PKDD 2016 Demo Track
ItisourgreatpleasuretointroducetheDemoTrackofECMLPKDD2016.Thisyear’s
track continues its tradition of providing a forum for researchers and practitioners to
demonstrate novel systems and research prototypes, using data mining and machine
learningtechniquesinavarietyofapplicationdomains.Besidesthelivedemonstrations
during the conference period, each selected demo is allocated a 4-page paper in the
proceedings.TheDemoTrackofECMLPKDD2016solicitedworkingsystemsbased
on state-of-the-art machine learning and data mining technology. Both innovative
prototypeimplementationsandmaturesystemswerewelcome,providedthattheyused
machinelearning techniquesandknowledge discoveryprocessesina realsetting.The
evaluation criteria encompassed innovation, interestingness for the target users, and
whetheritwouldbeofinterestmainlyforresearchers,mainlyforpractitioners,orboth.
Each submission was evaluated by at least three reviewers. This year we received 29
submissions.SixteendemoswerepresentedattheDemoSessionduringtheconference
in Riva del Garda. The accepted demos cover a wide range of machine learning and
dataminingtechniques,aswellasaverydiversesetofreal-worldapplicationdomains.
The success of the Demo Track of ECML PKDD 2016 is due to the effort of several
people. First and foremost, we thank the authors for their submissions and their
engagementinturningdataminingandmachinelearningmethodstosoftwarethatcan
be presented and tried by others. We would like to thank all members of our Program
Committee for helping us in the difficult task of selecting the most interesting sub-
missions. Finally, we would like to thank the ECML PKDD General Chairs and the
ProgramChairsforentrustinguswiththistrack,andthewholeOrganizingCommittee
forthepracticalsupportandthelogisticsfortheDemoTrack.Wehopethatthereaders
will enjoy this set of short papers and the demonstrated systems, and that the Demo
Session will inspire further ECML PKDD participants to turn their research ideas into
working prototypes that canbe used byother researchers and practitioners inmachine
learning and data mining.
September 2016 Élisa Fromont
Nikolaj Tatti
Foreword to the ECML PKDD 2016 Industry Track
We are pleased to present the proceedings of the Industrial, Governmental, and NGO
Track of ECML PKDD 2016. This track aims at bringing together participants from
academia, industry, government, and NGOs (non-governmental organizations) in a
venue that promotes industrial experiences and real-world applications of machine
learning and data science.
The program included two invited talks given by Michael May (Siemens) and
Matthias Seeger (Amazon), and 10 high-quality papers featuring the technical talks.
Given a total of 50 submissions, this year’s industrial track was highly selective: only
10 papers could be accepted for publication and for presentation at the conference;
corresponding to an acceptance rate of 20 %. Each of the 50 submissions was thor-
oughlyreviewed,andacceptedpaperswerechosenbothfortheiroriginalityandforthe
application they promoted.
The accepted papers focus on topics ranging from machine learning methods and
data science processes to dedicated applications. Topics covered include time series
mining and multi-target classification, visualization, software engineering, robotics,
bioinformatics, steel production, grammar-based text analysis for purposes such as
plagiarism or bible analysis, music recommendation, search task extraction, crowd-
sourcing and social networks, and discrimination discovery.
We thank all the authors who submitted the 50 papers for their work and effort to
bringmachinelearninganddatasciencetoindustry.WealsothankallthePCmembers
for their substantial efforts to guarantee the quality of these proceedings.
Wehopethatthisprogramwillinspirethegrowthofmachinelearninginallareasof
industry.
September 2016 Björn Bringmann
Gemma Garriga
Volker Tresp
Foreword to the ECML PKDD 2016 Nectar Track
The goal of the ECML PKDD 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 already published in related con-
ferences and journals. Submissions describing work that summarizes a line of work
comprising older and more recent papers were particularly encouraged. Authors were
invited to submit 4-page summaries of their published work.
We received 28 submissions, each of which was reviewed by two or three PC
members. Thirteen submissions were selected for inclusion in the proceedings and
presentation at the conference. The accepted papers range from interesting and
important applications to data mining and machine learning methods and processes.
Topics covered include methods and applications for time series mining and multi-
target classification, visualization, software engineering, robotics, bioinformatics, steel
production, grammar-based text analysis for purposes such as plagiarism or bible
analysis, music recommendation, search task extraction, crowdsourcing and social
networks, and discrimination discovery. The papers illustrate how the questions and
methods of these areas pose new challenges for data mining and machine learning,
thereby contributing also to the development of these core fields of ECML PKDD.
We thank all authors of submitted papers and all PC members for their excellent
work. Wearealso verygrateful totheECMLPKDDGeneral Chairs andtheProgram
Chairs for entrustinguswith this track.We hopethat thereaders willenjoy thisset of
short papers and their pointers to work at the intersection of machine learning/data
mining and their manifold application areas, and that the papers, presentations, and
discussions will inspire further work in the different disciplines and at their joint
boundaries.
September 2016 Bettina Berendt
Pauli Miettinen
Organization
ECML PKDD 2016 Organization
General Chairs
Andrea Passerini University of Trento, Italy
Fosca Giannotti National Research Council (ISTI-CNR), Italy
Program Chairs
Paolo Frasconi University of Florence, Italy
Niels Landwehr University of Potsdam, Germany
Giuseppe Manco National Research Council (ICAR-CNR), Italy
Jilles Vreeken Cluster of Excellence MMCI, Saarland University
& Max Planck Institute for Informatics, Germany
Journal Track Chairs
Thomas Gärtner University of Nottingham, UK
Mirco Nanni National Research Council (ISTI-CNR), Italy
Andrea Passerini University of Trento, Italy
Céline Robardet National Institute of Applied Science in Lyon, France
Industrial Track Chairs
Björn Bringmann Deloitte GmbH, Germany
Gemma Garriga Allianz SE Munich, Germany
Volker Tresp SiemensAG&LudwigMaximilianUniversityofMunich,
Germany
Local Organization Chairs
Simone Marinai University of Florence, Italy
Gianluca Corrado University of Trento, Italy
Katya Tentori University of Trento, Italy
XII Organization
Workshop and Tutorial Chairs
Matthijs van Leeuwen Leiden University, Netherlands
Fabrizio Costa University of Freiburg, Germany
Albrecht Zimmermann University of Caen, France
Awards Committee Chairs
Toon Calders Free University of Bruxelles, Belgium
Hendrik Blockeel University of Leuven, Belgium
Nectar Track Chairs
Bettina Berendt KU Leuven, Belgium
Pauli Miettinen Max Planck Institute for Informatics, Germany
Demo Chairs
Nikolaj Tatti Aalto University School of Science, Finland
Élisa Fromont Jean Monnet University, France
Discovery Challenge Chairs
Elio Masciari National Research Council (ICAR-CNR), Italy
Alessandro Moschitti Qatar Computing Research Institute, HBKU,
Qatar & University of Trento, Italy
Sponsorship Chairs
Michelangelo Ceci University of Bari, Italy
Chedy Raïssi Inria, France
Publicity and Social Media Chairs
Olana Missura University of Bonn, Germany
Nicola Barbieri Yahoo!, UK
Gianluca Corrado University of Trento, Italy
PhD Forum Chairs
Leman Akoglu Stony Brook University, USA
Tijl De Bie Ghent University, Belgium
