Discovery Science: 24th International Conference, DS 2021, Halifax, NS, Canada, October 11–13, 2021, Proceedings (Lecture Notes in Computer Science)

474 Pages·2021·43.57 MB·English

by  Carlos Soares (editor), Luis Torgo (editor)

Carlos Soares
Luis Torgo (Eds.)
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I Discovery Science
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24th International Conference, DS 2021
Halifax, NS, Canada, October 11–13, 2021
Proceedings
123
Lecture Notes in Artificial Intelligence 12986
Subseries of Lecture Notes in Computer Science
SeriesEditors
RandyGoebel
UniversityofAlberta,Edmonton,Canada
YuzuruTanaka
HokkaidoUniversity,Sapporo,Japan
WolfgangWahlster
DFKIandSaarlandUniversity,Saarbrücken,Germany
FoundingEditor
JörgSiekmann
DFKIandSaarlandUniversity,Saarbrücken,Germany
Moreinformationaboutthissubseriesathttp://www.springer.com/series/1244
·
Carlos Soares Luis Torgo (Eds.)
Discovery Science
24th International Conference, DS 2021
Halifax, NS, Canada, October 11–13, 2021
Proceedings
Editors
CarlosSoares LuisTorgo
UniversidadedoPortoandFraunhofer DalhousieUniversity
PortugalAICOS Halifax,NS,Canada
Porto,Portugal
ISSN 0302-9743 ISSN 1611-3349 (electronic)
LectureNotesinArtificialIntelligence
ISBN 978-3-030-88941-8 ISBN 978-3-030-88942-5 (eBook)
https://doi.org/10.1007/978-3-030-88942-5
LNCSSublibrary:SL7–ArtificialIntelligence
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Preface
This volume contains the papers selected for presentation at the 24th International
Conference on Discovery Science (DS 2021), which was organized to be held in
Halifax, Canada, during October 11–13, 2021. Due to the restrictions associated with
theCOVID-19pandemic,theconferencewasmovedonlineandheldvirtuallyoverthe
sametimeperiod.
DS is a conference series that started in 1986. Held every year, DS continues its
tradition as the unique venue for the latest advances in the development and analysis
ofmethodsfordiscoveringscientificknowledge,comingfrommachinelearning,data
mining, and intelligent data analysis, along with their application in various scientific
domains.Inparticular,majorareasselectedforDS2021includedthefolllowing:appli-
cations (including a relevant number of papers addressing the COVID-19 pandemic),
classification, data streams, feature selection, graph and network mining, neural net-
works and deep learning, preferences, recommender systems, representation learning,
responsibleartificialintelligence,andspatial,temporalandspatiotemporaldata.
DS2021received76internationalsubmissionsthatwerecarefullyreviewedbythree
ormoreProgramCommittee(PC)membersorexternalreviewers,withafewexceptions.
Afterarigorousreviewingprocess,15regularpapersand21shortpaperswereaccepted
forpresentationattheconferenceandpublicationintheDS2021volume.
Wewouldliketosincerelythankallpeoplewhohelpedthisvolumecomeintobeing
andmadeDS2021asuccessfulandexcitingevent.Inparticular,wewouldliketoexpress
ourappreciationfortheworkoftheDS2021PCmembersandexternalreviewerswho
helpedassurethehighstandardofacceptedpapers.Wewouldliketothankallauthors
ofsubmissionstoDS2021,withoutwhoseworkitwouldnothavebeenpossibletohave
suchhigh-qualitycontributionsintheconference.
WearegratefultotheSteeringCommitteechair,SašoDžeroski,forhisextraordinary
support in critical decisions concerning the event plan, particularly important in these
challenging times. We are also very grateful to the Program Committee chairs of DS
2020,AnnalisaAppiceandGrigoriosTsoumakas,foralltheinformationprovided,which
made the whole organization much easier. We wish to express our thanks to the local
organizationchairs,DavidLangstroth,NunoMoniz,PaulaBranco,VitorCerqueira,and
Yassine Baghoussi, for their support and incredible work. We would like to express
our deepest gratitude to all those who served as organizers, session chairs, and hosts,
who made great efforts to meet the online challenge to make the virtual conference
a real success. Finally, our thanks are due to Alfred Hofmann and Anna Kramer of
Springer for their continuous support and work on the proceedings. We are grateful
to Springer for a special issue on Discovery Science to be published in the Machine
Learningjournal.Allauthorsweregiventhepossibilitytoextendandreworkversions
of their papers presented at DS 2021 for a chance to be published in this prestigious
journal.ForDS2021,SpringeralsosupportedaBestStudentPaperAward,whichwas
giventoBartBussmannandhisco-authors,JannesNysandStevenLatré,fortheirpaper
“NeuralAdditiveVectorAutoregressionModelsforCausalDiscoveryinTimeSeries.”
vi Preface
This paper presents high quality work on a very relevant topic and is complemented
with the materials to reproduce it. We would like to congratulate the authors for this
achievement.
September2021 CarlosSoares
LuisTorgo
Organization
ProgramCommitteeChairs
CarlosSoares UniversidadedoPortoandFraunhoferPortugalAICOS,
Portugal
LuisTorgo DalhousieUniversity,Canada
ProgramCommittee
MartinAtzmueller TilburgUniversity,TheNetherlands
ColinBellinger NationalResearchCouncilofCanada,Canada
PaulaBranco OttawaUniversity,Canada
AlbertoCano VirginiaCommonwealthUniversity,USA
DanielCastroSilva UniversityofPorto,Portugal
MichelangeloCeci UniversityofBariAldoMoro,Italy
VictorCerqueira DalhousieUniversity,Canada
BrunoCremilleux UniversityofCaenNormandy,France
NicolaDiMauro UniversityofBariAldoMoro,Italy
IvicaDimitrovski Ss.CyrilandMethodiusUniversityinSkopje,North
Macedonia
WouterDuivesteijn EindhovenUniversityofTechnology,TheNetherlands
SašoDžeroski JožefStefanInstitute,Slovenia
JohannesFürnkranz JohannesKeplerUniversityLinz,Austria
MohamedGaber BirminghamCityUniversity,UK
DraganGamberger RudjerBoškovic´ Institute,Croatia
MancoGiuseppe ItalianNationalResearchCouncil,Italy
KouichiHirata KyushuInstituteofTechnology,Japan
DinoIenco Irstea,France
NathalieJapkowicz AmericanUniversity,USA
StefanKramer JohannesGutenbergUniversityMainz,Germany
VincenzoLagani IliaStateUniversity,Georgia
PedroLarranaga UniversityofMadrid,Spain
NadaLavracˇ JožefStefanInstitute,Slovenia
TomislavLipic RudjerBoškovic´ Institute,Croatia
GjorgjiMadjarov Ss.CyrilandMethodiusUniversityinSkopje,North
Macedonia
RafaelGomesMantovani FederalUniversityofTechnology–Paraná,Brazil
ElioMasciari InstituteforHighPerformanceComputingand
Networking,Italy
NunoMoniz UniversityofPorto,Portugal
AnnaMonreale UniversityofPisa,Italy
viii Organization
CatarinaOliveira PortucalenseUniversity,Portugal
SageevOore DalhousieUniversityandVectorInstitute,Canada
RitaP.Ribeiro UniversityofPorto,Portugal
GeorgePapakostas InternationalHellenicUniversity,Greece
RuggeroG.Pensa UniversityofTurin,Italy
PedroPereiraRodrigues UniversityofPorto,Portugal
BernhardPfahringer UniversityofWaikato,NewZealand
GianvitoPio UniversityofBariAldoMoro,Italy
PascalPoncelet LIRMMMontpellier,France
JanRamon Inria,France
AndréL.D.Rossi UniversidadeEstadualPaulista,Brazil
KazumiSaito UniversityofShizuoka,Japan
TomislavSmuc RudjerBoškovic´ Institute,Croatia
MarinaSokolova UniversityofOttawaandDalhousieUniversity,Canada
JerzyStefanowski PoznanUniversityofTechnology,Poland
LuisFilipeTeixeira UniversityofPorto,Portugal
HernaViktor UniversityofOttawa,Canada
BaghoussiYassine UniversityofPorto,Portugal
AlbrechtZimmermann UniversityofCaenNormandy,France
AdditionalReviewers
AnaMestrovic JoãoAlves
DanielaSantos LeonardoFerreira
EmanuelGuberovic MihaKeber
FabrizioLoScudo
NarjesDavari
FrancescaPratesi
NimaDehmamy
FrancescoS.Pisani
NunziatoCassavia
FrancescoSpinnato
IsabelRio-Torto PaoloMignone
IvanGrubisic RafaelaLeal
JoãoAlmeida RobertoInterdonato
Contents
Applications
AutomatedGradingofExamResponses:AnExtensiveClassification
Benchmark ........................................................... 3
JimmyLjungman, VanessaLislevand, JohnPavlopoulos,
AlexandraFarazouli,ZedLee,PanagiotisPapapetrou,andUnoFors
AutomaticHuman-LikeDetectionofCodeSmells ......................... 19
ChitsuthaSoomlek,JanN.vanRijn,andMarcelloM.Bonsangue
HTML-LSTM:InformationExtractionfromHTMLTablesinWebPages
UsingTree-StructuredLSTM ........................................... 29
KazukiKawamuraandAkihiroYamamoto
Predicting Reach to Find Persuadable Customers: Improving Uplift
ModelsforChurnPrevention ............................................ 44
ThéoVerhelst, JeevanShrestha, DenisMercier,
Jean-ChristopheDewitte,andGianlucaBontempi
Classification
ASemi-supervisedFrameworkforMisinformationDetection ................ 57
YueyangLiu,ZoisBoukouvalas,andNathalieJapkowicz
AnAnalysisofPerformanceMetricsforImbalancedClassification ........... 67
Jean-GabrielGaudreault,PaulaBranco,andJoãoGama
CombiningPredictionsUnderUncertainty:TheCaseofRandomDecision
Trees ................................................................ 78
FlorianBusch,MoritzKulessa,EneldoLozaMencía,andHendrikBlockeel
Shapley-ValueDataValuationforSemi-supervisedLearning ................. 94
ChristieCourtnageandEvgueniSmirnov
DataStreams
ANetworkIntrusionDetectionSystemforConceptDriftingNetwork
TrafficData ........................................................... 111
GiuseppinaAndresini, AnnalisaAppice, CorradoLoglisci,
VincenzoBelvedere,DomenicoRedavid,andDonatoMalerba