Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part III

473 Pages·2017·41.45 MB·English

by  Yasemin Altun

Yasemin Altun · Kamalika Das
Taneli Mielikäinen · Donato Malerba
Jerzy Stefanowski · Jesse Read
Marinka Žitnik · Michelangelo Ceci
Sašo Džeroski (Eds.)
Machine Learning and
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European Conference, ECML PKDD 2017
Skopje, Macedonia, September 18–22, 2017
Proceedings, Part III
123
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Lecture Notes in Arti cial Intelligence 10536
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
Yasemin Altun Kamalika Das
(cid:129)
ä
Taneli Mielik inen Donato Malerba
(cid:129)
Jerzy Stefanowski Jesse Read
(cid:129)
Ž
Marinka itnik Michelangelo Ceci
(cid:129)
š ž
Sa o D eroski (Eds.)
Machine Learning and
Knowledge Discovery
in Databases
European Conference, ECML PKDD 2017
–
Skopje, Macedonia, September 18 22, 2017
Proceedings, Part III
123
Editors
YaseminAltun Jesse Read
Google Research Laboratoire d’ Informatique (LIX)
Google Inc. ÉcolePolytechnique
Zurich Palaiseau
Switzerland France
Kamalika Das Marinka Žitnik
NASA AmesResearch Center Department ofComputer Science
Mountain View StanfordUniversity
USA Stanford
USA
TaneliMielikäinen
Oath Michelangelo Ceci
Sunnyvale Universitàdegli Studi diBari AldoMoro
USA Bari
Italy
Donato Malerba
Department ofComputer Science Sašo Džeroski
University of Bari Aldo Moro Jožef StefanInstitute
Bari Ljubljana
Italy Slovenia
JerzyStefanowski
Institute of Computing Science
Poznan University of Technology
Poznan
Poland
ISSN 0302-9743 ISSN 1611-3349 (electronic)
Lecture Notesin Artificial Intelligence
ISBN 978-3-319-71272-7 ISBN978-3-319-71273-4 (eBook)
https://doi.org/10.1007/978-3-319-71273-4
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Preface
This year was the 10th edition of ECML PKDD as a single conference. While ECML
and PKDD have been organized jointly since 2001, they only officially merged in
2008. Following the growth of the field and the community, the conference has
diversified and expanded over the past decade in terms of content, form, and atten-
dance. This year, ECML PKDD attracted over 600 participants.
Wewereproudtopresentarichscientificprogram,includinghigh-profilekeynotes
and many technical presentations in different tracks (research, journal, applied data
science, nectar, and demo), fora (EU projects, PhD), workshops, tutorials, and dis-
covery challenges. We hope that this provided ample opportunities for exciting
exchanges of ideas and pleasurable networking.
Manypeopleputincountlesshoursofworktomakethiseventhappen:Tothemwe
express our heartfelt thanks. This includes the organization team, i.e., the program
chairs of the different tracks and fora, workshops and tutorials, and discovery chal-
lenges, as well as the awards committee, production and public relations chairs, local
organizers, sponsorship chairs, and proceedings chairs. In addition, we would like to
thank the program committees of the different conference tracks, the organizers of the
workshops and their respective committees, the Cankarjev Dom congress agency, and
the student volunteers. Furthermore, many thanks to our sponsors for their generous
financial support. We would also like to thank Springer for their continuous support,
Microsoft for allowing us to use their CMT software for conference management, the
European project MAESTRA (ICT-2013-612944), as well as the ECML PKDD
Steering Committee (for their suggestions and advice). We would like to thank the
organizing institutions: the Jožef Stefan Institute (Slovenia), the Ss. Cyril and
Methodius University in Skopje (Macedonia), and the University of Bari Aldo Moro
(Italy).
Finally, thanks to all authors who submitted their work for presentation at
ECMLPKDD2017.Last,butcertainlynotleast,wewouldliketothanktheconference
participants who helped us make it a memorable event.
September 2017 Sašo Džeroski
Michelangelo Ceci
Foreword to the ECML PKDD 2017
Applied Data Science Track
WearepleasedtopresenttheproceedingsoftheAppliedDataScience(ADS)Trackof
ECML PKDD 2017. This track aims to bring together participants from academia,
industry, governments, and NGOs (non-governmental organizations) in a venue that
highlights practical and real-world studies of machine learning, knowledge discovery,
and data mining. Novel and practical ideas, open problems in applied data science,
descriptionofapplication-specificchallenges,anduniquesolutionsadoptedinbridging
thegapbetweenresearchandpracticearesomeoftherelevanttopicsforwhichpapers
havebeensubmittedandacceptedinthistrack.Thisyear’sAppliedDataScienceTrack
included 27 accepted paper presentations distributed across six sessions. Given a total
of 93 submissions, this year’s track was highly selective: Only 27 papers could be
accepted for publication and for presentation at the conference, corresponding to an
acceptance rate of 29%. Each of the 93 submissions was thoroughly reviewed, and
accepted papers were chosen both for their originality and for the application they
promoted. The accepted papers focus on topics ranging from machine-learning meth-
odsanddata scienceprocessestodedicatedapplications.Topics covered includedeep
learning, time series mining, text mining, for a variety of applications such as
e-commerce, fraud detection, social good, ecology, experiment design, and social
networkanalysis.Wethankalltheauthorswhosubmittedthe93papersfortheirwork
andefforttobringmachinelearningtosolvemanyinterestingproblems.Wealsothank
all the Program Committee members of the ADS track for their substantial efforts to
guaranteethequalityoftheseproceedings.Wehopethatthisprogramwasenjoyableto
both academics and practitioners alike, and fostered the beginning of new industry–
academia collaborations.
September 2017 Yasemin Altun
Kamalika Das
Taneli Mielikäinen
Foreword to the ECML PKDD 2017 Nectar Track
We are pleased to present the proceedings of the Nectar Track of the ECML PKDD
2017conferenceheldinSkopje.Thistrack,whichstartedin2012,providesaforumfor
thediscussionofrecenthigh-qualityresearchresultsatthefrontierofmachinelearning
and data mining with other disciplines, which have been already 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.
Particularly welcome were papers illustrating the pervasiveness of data-driven explo-
ration and modelling in science, technology, and society, as well as innovative
applications, and also theoretical results. Authors were invited to submit four-page
summaries of their previously published work.
We received 25 submissions and each of them was thoroughly reviewed by two
ProgramCommittee(PC)members.Finally,tenpaperswereselectedforpublicationin
the proceedings and presentation during the conference. The accepted papers cover a
wide range of machine learning and data mining methods, as well as quite diverse
domainsof applications. The topics cover, among others, automatic music generation,
music chord prediction, phenotype inference from biomedical texts and genomic
databases, new data-driven approaches for finding a parking space in cities,
process-based modelling to construct dynamical systems, advances in kernel-based
graph classification, user interactions and influence in social networks, efficient
exploitationoftreeensemblesinWebsearchanddocumentranking,datacleaningwith
AI planning solvers, and applications of predictive clustering trees to image analysis.
We take this opportunity to thank all authors for submitting their papers to the
NectarTrack.WealsowishtoexpressourgratitudetoallPCmemberswhohelpedus
in the reviewing process, providing insightful feedback that helped the authors of
acceptedpaperstopreparegoodpresentationsduringtheconference.Finally,wewould
liketothanktheECMLPKDDgeneralchairsandtheothermembersoftheOrganizing
Committeefortheirexcellentco-operationandsupportforallourefforts.Wehopethat
thereaders willenjoytheseshortpapersandthatthepapers,conferencepresentations,
and discussions will inspire further interesting research at the boundaries of machine
learning and data mining with many other interesting fields.
September 2017 Donato Malerba
Jerzy Stefanowski
Foreword to the ECML PKDD 2017 Demo Track
We present, with great pleasure, the Demo Track of ECML PKDD 2017. Since its
inception, this Demo Track is among the major forums in the field for presenting
state-of-the-artdataminingandmachinelearningsystemsandresearchprototypes,and
for disseminating new methods and techniques in a variety of application domains.
Eachselecteddemowaspresentedattheconferenceandallocatedafour-pagepaperin
the proceedings.
The evaluation criteria encompassed innovation and technical advances, meeting
novelchallenges,andthepotentialimpactandinterestforresearchersandpractitioners
in the machine learning and data-mining community. Each submission was first
reviewed by at least two expert referees, with a majority receiving three reviews.
Consensusoneachpaperwasreachedthroughdiscussionbetweenthedemochairs.In
total, 52 reviews were made, and from 17 original submissions 10 were accepted for
publicationintheconferenceproceedingsandpresentationatthedemosessionsduring
the conference in Skopje. The accepted demonstration papers cover a wide range of
machine learning and data mining techniques, as well as a very diverse set of
real-world application domains. We believe the review system was successful in
ensuring that the accepted work is of high quality and suited for publication in the
track.
Wethank all authors for submitting their work, without which thistrack wouldnot
be possible. We are deeply grateful to our Program Committee for volunteering their
timeandexpertise.TheircontributionisatthecoreofthescientificqualityoftheDemo
Track.TheexpertProgramCommitteeincludedamixofexperiencedindividualsfrom
previous years as well as experts newly recruited to ensure broad technical expertise
andtopromoteinclusivityofvariousdataminingandmachinelearningresearchareas.
Finally, we wish to thank the general chairs and the program chairs for entrusting us
withthistrackandprovidinguswiththeirexpertadvice.Wehopethatthereaderswill
enjoy this set of short papers and that the demonstrated systems, prototypes, and
librariesofthistrackwillinspireinteractionanddiscussionthatwillbevaluabletoboth
the authors and the community at large.
September 2017 Jesse Read
Marinka Zitnik
Organization
ECML PKDD 2017 Organization
Conference Chairs
Michelangelo Ceci University of Bari Aldo Moro, Italy
Sašo Džeroski Jožef Stefan Institute, Slovenia
Program Chairs
Michelangelo Ceci University of Bari Aldo Moro, Italy
Jaakko Hollmén Aalto University, Finland
Ljupčo Todorovski University of Ljubljana, Slovenia
Celine Vens KU Leuven Kulak, Belgium
Journal Track Chairs
Kurt Driessens Maastricht University, The Netherlands
Dragi Kocev Jožef Stefan Institute, Slovenia
Marko Robnik-Šikonja University of Ljubljana, Slovenia
Myra Spiliopoulu Magdeburg University, Germany
Applied Data Science Track Chairs
Yasemin Altun Google Research, Switzerland
Kamalika Das NASA Ames Research Center, USA
Taneli Mielikäinen Yahoo! USA
Local Organization Chairs
Ivica Dimitrovski Ss. Cyril and Methodius University, Macedonia
Tina Anžič Jožef Stefan Institute, Slovenia
Mili Bauer Jožef Stefan Institute, Slovenia
Gjorgji Madjarov Ss. Cyril and Methodius University, Macedonia
Workshops and Tutorials Chairs
Nathalie Japkowicz American University, USA
Panče Panov Jožef Stefan Institute, Slovenia