Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part III PDF
Preview Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part III
Yasemin Altun · Kamalika Das Taneli Mielikäinen · Donato Malerba Jerzy Stefanowski · Jesse Read Marinka Žitnik · Michelangelo Ceci Sašo Džeroski (Eds.) Machine Learning and 6 3 Knowledge Discovery 5 0 1 I A in Databases N L European Conference, ECML PKDD 2017 Skopje, Macedonia, September 18–22, 2017 Proceedings, Part III 123 fi 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 LibraryofCongressControlNumber:2017961799 LNCSSublibrary:SL7–ArtificialIntelligence ©SpringerInternationalPublishingAG2017 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartofthe material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodologynow knownorhereafterdeveloped. Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublication doesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevant protectivelawsandregulationsandthereforefreeforgeneraluse. Thepublisher,theauthorsandtheeditorsaresafetoassumethattheadviceandinformationinthisbookare believedtobetrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsortheeditors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregardtojurisdictionalclaimsin publishedmapsandinstitutionalaffiliations. Printedonacid-freepaper ThisSpringerimprintispublishedbySpringerNature TheregisteredcompanyisSpringerInternationalPublishingAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland 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
Description:The list of books you might like
