Andrea Cal`ı Maria-Esther Vidal (Eds.) AMW2015 Alberto Mendelzon International Workshop on ...

231 Pages·2015·4.71 MB·English

Andrea Cal`ı
Maria-Esther Vidal (Eds.)
AMW2015
Alberto Mendelzon International Workshop
on Foundations of Data Management
Lima, Peru´, May 6th-8th, 2015
Proceedings
Copyright c 2015 for the individual papers by the papers’ authors. Copying permitted
(cid:13)
onlyforprivateandacademicpurposes. Thisvolumeispublishedandcopyrightedbyits
editors. Re-publicationofmaterialfromthisvolumerequirespermissionbythecopyright
owners.
Editors’addresses:
BirkbeckCollege,UniversityofLondon,UK
[email protected];
UniversidadSimo´nBol´ıvar
DepartmentofComputerScience
ValledeSartenejas
Caracas1086,Venezuela
[email protected]
Preface
TheAlbertoMendelzonWorkshop(AMW)isaLatinAmericaninitiativestartedin2006
to honor the memory of Alberto Mendelzon, who gave a significant contribution to the
field of data management. The AMW is a research venue for top-quality research on
foundationsofdatamanagement;whilefocusedespeciallyonLatinAmericanstudentsand
scholars, the workshop is open to submissions from anywhere and it has so far gathered
someoftheworld’sbestresearchersinthefield.
Thisvolumecontainspapersacceptedatthe9theditionoftheAMW,heldinLima,Peru´,
fromthe6thtothe8thofMay,2015.Thecallforpapersofthiseditionrequestedtwotypes
ofsubmissions:regularandshortpapers,wherethelatterwereintendedtopresentongoing
research,resultspreviouslypublished,ordatamanagementapplications. Witharound40
submissions, we could put up an exciting program, which gave raise to discussions and
new ideas. Despite the beauties of Lima, including its sophisticated cuisine and drinks,
the attendees and the organizers worked hard and made the AMW 2015 a great success,
both from the scientific and organizational point of view. The school, which took place
beforetheworkshop,providedlocalstudentswithtutorialswhosequalitywasonparwith
those at the best conferences in the area. The invited talks at the workshop were also
certainlyworld-classandgivenbyleadingresearchers: GuyvandenBroeck(KULeuven,
Belgium),WagnerMeiraJr(UniversidadeFederaldeMinasGerais,Brazil),DanOlteanu
(UniversityofOxford,UK),andVictorVianu(UCSanDiego,USA).
For what we are proud to call a very exciting scientific event, we would like to warmly
thank, in no particular order: the authors of the papers, the Program Committee and the
externalreviewers,thelocalorganizers,theAMWSchoolcommittee,theSteeringCom-
mittee, the General Chair, and the local supporting institutions. Without the effort of all
theabove,theAMW2015couldnothavebeensuccessful.
We are also looking forward to the next editions of the Alberto Mendelzon Workshop,
whichhasbecomeanestablishedandhigh-qualityvenueintheareaofDataManagement.
Lima,May2015
AndreaCal`ı1
Maria-EstherVidal
1AndreaCal`ıacknowledgessupportfromtheEPSRCgrant“Logic-basedIntegrationandQueryingofUnin-
dexedData”(EP/E010865/1)
GeneralChair
PabloBarcelo´ (UniversidaddeChile,Chile)
PCChairs
AndreaCali,BirkbeckCollege,UniversityofLondon,UK)
Maria-EstherVidal,UniversidadSimo´nBol´ıvar,Venezuela
ProgramCommittee
CristinaDutraDeAguiarCiferri(UniversidadedeSaoPaulo,Brazil)
OscarCorcho(UniversidadPolitecnicadeMadrid,Spain)
IsabelCruz(UniversityofIlinnoisatChicago,USA)
AmelieGheerbrant(UniversiteParisVIIDenisDiderot,France)
ParkeGodfrey(YorkUniversity,Canada)
SergioGreco(UniversitadellaCalabria,Italy)
ClaudioGutierrez(UniversidaddeChile)
MauricioA.Hernandez-Sherrington(IBMResearchAlmaden,USA)
AidanHogan(UniversidaddeChile)
ElizabethLeon(UniversidadNacionaldeColombia)
JorgeLobo(ICREAandUniversidadPompeuFabra,Spain)
MariaVaninaMartinez(UniversidadNacionaldelSur,Argentina)
FilipMurlak(UniversityofWarsaw,Poland)
MauricioOsorio(UniversidaddelasAmericasPuebla,Mexico)
ReinhardPichler(ViennaUniversityofTechnology,Austria)
AndreasPieris(ViennaUniversityofTechnology,Austria)
AlessandroProvetti(UniversityofMessina,Italy)
JarekSzlichta(UniversityofOntario,Canada)
ReginaPaolaTiconaHerrera(UniversitedePauetdesPaysdel’Adour,France)
RiccardoTorlone(UniversitaRomaTre)
PeterWood(Birkbeck,UniversityofLondon,UK)
SteeringCommittee
RicardoBaeza-Yates(YahooResearch,Spain)
PabloBarcelo(UniversidaddeChile,Chile)
LeopoldoBertossi(CarletonUniversity,Canada)
MarianoConsens(UniversityofToronto,Canada)
AlbertoH.F.Laender(UniversidadeFederaldeMinasGerais,Brazil)
JorgePerez(UniversidaddeChile,Chile)
LocalSupportingInstitutions
UniversidadMayordeSanMarcos
FacultaddeIngenier´ıadeSistemaseInforma´tica
•
FacultaddeCienciasMatema´ticas
•
UniversidadRicardoPalma
FacultaddeIngenier´ıaInforma´tica
•
UniversidadCato´licadeSanPablo
EscuelaProfesionaldeCienciadelaComputacio´n
•
SociedadPeruanadeComputacio´n
IEEE-Seccio´nPeu´
ColegiodeMatema´ticosdePeu´
Contents
ADatabaseFrameworkforClassifierEngineering
BennyKimelfeldandChristopherRe 1
ExtendingDatalogwithAnalyticsinLogicBlox
MolhamAref,BennyKimelfeld,EmirPasalic1andNikolaosVasiloglou 6
TowardsReconcilingSPARQLandCertainAnswers(ExtendedAbstract)
ShqiponjaAhmetaj,WolfgangFischl,ReinhardPichler,MantasSimkusandSebas-
tianSkritek 12
EfficientEvaluationofWell-designedPatternTrees(ExtendedAbstract)
PabloBarcelo,ReinhardPichlerandSebastianSkritek 18
ApproximationAlgorithmsforSchema-MappingDiscoveryfromDataExamples
BaldertenCate,PhokionG.Kolaitis,KunQianandWang-ChiewTan 24
IMGpedia: AProposaltoEnrichDBpediawithImageMeta-Data
BenjaminBustosandAidanHogan 35
FromClassicaltoConsistentQueryAnsweringunderExistentialRules
ThomasLukasiewicz,MariaVaninaMartinez,AndreasPierisandGerardoI.Simari 40
FindingSimilarProductsinE-commerceSitesBasedonAttributes
UriqueHoffmann,AltigrandaSilva,andMoisesCarvalho 46
EntityMatching: ACaseStudyintheMedicalDomain
LuizF.M.Carvalho,AlbertoH.F.LaenderandWagnerMeiraJr. 57
UsingStatisticsforComputingJoinswithMapReduce
TheresaCsar,ReinhardPichler,EmanuelSallingerandVadimSavenkov 69
TriAL-QL:DistributedProcessingofNavigationalQueries
MartinPrzyjaciel-Zablocki,AlexanderSchatzleandAdrianLange 75
OnAxiomatizationandInferenceComplexityoveraHierarchyofFunctionalDe-
pendencies
JaroslawSzlichta,LukaszGolabandDiveshSrivastava 79
PPDL:ProbabilisticProgrammingwithDatalog
BaldertenCate,BennyKimelfeldandDanOlteanu 91
CONTENTS
Implementing Graph Query Languages over Compressed Data Structures: A
ProgressReport
Nicola´sLehmannandJorgePe´rez 96
Tractable Query Answering and Optimization for Extensions of Weakly-Sticky
Datalog
±
MostafaMilaniandLeopoldoBertossi 101
Saturation,Definability,andSeparationforXPathonDataTrees
SergioAbriol,MaraEmiliaDescotte,andSantiagoFigueira 106
Random-WalkClosenessCentralitySatisfiesBoldi-VignaAxioms
RicardoMoraandClaudioGutierrez 110
ExploitingSemanticstoPredictPotentialNovelLinksfromDenseSubgraphs
AlejandroFlores,Maria-EstherVidalandGuillermoPalma 121
OntheCALMPrincipleforBSPComputation
MatteoInterlandiandLetiziaTanca 131
ChaseTerminationforGuardedExistentialRules
MarcoCalautti,GeorgGottlobandAndreasPieris 142
Dataintegrationwithmanyheterogeneoussourcesanddynamictargetschemas
(extendedabstract)
LuigiBellomarini,PaoloAtzeniandLucaCabibbo 148
Rewriting-basedCheckofChaseTermination
MarcoCalautti,SergioGreco,CristianMolinaroandIrinaTrubitsyna 156
NavigationalQueriesBasedonFrontier-GuardedDatalog: PreliminaryResults
MeghynBienvenu,MagdalenaOrtizandMantasSimkus 162
LDQL:ALanguageforLinkedDataQueries
OlafHartig 172
IntuitionisticDataExchange
GostaGrahne,AliMoallemiandAdrianOnet 184
A preliminary investigation into SPARQL query complexity and federation in
Bio2RDF
CarlosBuil-Aranda,MartinUgarte,MarceloArenasandMichelDumontier 196
CONTENTS
KeywordSearchintheDeepWeb
AndreaCali,DavideMartinenghiandRiccardoTorlone 205
ImplementingData-CentricDynamicSystemsoveraRelationalDBMS
DiegoCalvanese,MarcoMontali,FabioPatriziandAndreyRivkin 209
DisentanglingtheNotionofDatasetinSPARQL
DanielHernandezandClaudioGutierrez 213
A Database Framework for Classifier Engineering
BennyKimelfeld1andChristopherRe´2
1 LogicBlox,Inc.andTechnion,Israel
2 StanfordUniversity
1 Introduction
In the design of machine-learning solutions, a critical and often the most resourceful
taskisthatoffeatureengineering[7,4],forwhichrecipesandtoolinghavebeendevel-
oped [3,7]. In this vision paper we embark on the establishment of database founda-
tionsforfeatureengineering.Weproposeaformalframeworkforclassification,inthe
context of a relational database, towards investigating the application of database and
knowledgemanagementtoassistwiththetaskoffeatureengineering.Wedemonstrate
theusefulnessofthisframeworkbyformallydefiningtwokeyalgorithmicchallenges
within:(1)separabilityreferstodeterminingtheexistenceoffeaturequeriesthatagree
with the given training examples, and (2) identifiability is the task of testing for the
property of independence among features (given as queries). Moreover, we give pre-
liminary results on these challenges, in the context of conjunctive queries. We focus
here on boolean features that are represented as ordinary database queries, and view
thisworkasthebasisofvariousfutureextensionssuchasnumericalfeaturesandmore
generalregressiontasks.
2 FormalFramework
We first present our formal framework for classification with binary features within a
relationaldatabase.
2.1 ClassifiersandLearning
Inthiswork,aclassifierisafunctionoftheform
γ : 1,1 n 1,1
{− } →{− }
wherenisanaturalnumberthatwecallthearityofγ.Aclassifierclassisa(possibly
infinite) family Γ of classifiers. We denote by Γ the restriction of Γ to the n-ary
n
classifiersinΓ.Ann-arytrainingcollectionisamultisetT ofpairs x,y wherex
1,1 n andy 1,1 .WedenotebyT thesetofalln-arytrahiningicollection∈s.
n
{− } ∈ {− }
AcostfunctionforaclassifierclassΓ isafunctionoftheform
c : n(Γn Tn) R 0
∪ × → ≥
(cid:0) (cid:1)
1
ADatabaseFrameworkforClassifierEngineering
whereR 0 isthesetofnonnegativenumbers.InthecontextofaclassifierclassΓ and
≥
a cost function c, learning a classifier is the task of finding a classifier γ Γ that
n
∈
minimizesc(γ,T),givenatrainingcollectionT T .
n
∈
We illustrate the above definitions on the important class of linear classifiers. An
n-arylinearclassifierisparameterizedbyavectorw Rn,isdenotedbyΛw,andis
definedasfollowsforalla 1,1 n. ∈
∈{− }
1 ifa w 0;
λ (a)=def · ≥
w
( 1 otherwise.
−
where “” denotes the operation of dot product. By Lin we denote the class of linear
·
classifiers.Anexampleofacostfunctionistheleastsquarecostlsq thatisgivenby
lsq(Λ ,T)=def (x w y)2
w
· −
hxX,yi∈T
fortheargumentsΛ Lin andT T .
w n n
∈ ∈
2.2 RelationalFormalism
Our relational terminology is as follows. A schema is a pair ( ,Σ), where is a
A A
signaturethatconsistsofrelationsymbols,andΣisasetoflogicalintegrityconstraints
over .EachrelationsymbolRhasanassociatedarity.WeassumeaninfinitesetConst
A
of constants. An instance I over a schema S = ( ,Σ) associates with every k-ary
relationsymbolR afinitesubsetRI ofConstkA,suchthatalltheconstraintsofΣ
∈ A
aresatisfied.TheactivedomainofaninstanceI,denotedadom(I),isthesetofallthe
constantsinConstthatarementionedinI.
LetSbeschema.Aquery(overS)isafunctionQthatisassociatedwithanarity
k,andthatmapseveryrelationinstanceI overSintoafinitesubsetQ(I)ofConstk.A
queryQ containsaqueryQifQ(I) Q(I)forallinstancesI overS;ifQ Q and
0 0 0
⊆ ⊆
Q QthenQandQ aresaidtobeequivalent.AqueryQisadditiveifforeverytwo
0 0
⊆
instancesI andI ,ifadom(I )andadom(I )aredisjoint,then
1 2 1 2
Q(I I )=Q(I ) Q(I ).
1 2 1 2
∪ ∪
AqueryclassisamappingthatassociateswitheveryschemaSaclassofqueriesover
S.Anexampleofaqueryclassisthatoftheconjunctivequeries.Aconjunctivequery
(CQ)isrepresentedbythelogicalformulaq(x)thathastheform
y[φ (x,y,d) φ (x,y,d)]
1 m
∃ ∧···∧
wherexandyaredisjointsequencesofvariables,disasequenceofconstants,andeach
φ isanatomicqueryoverS(i.e.,aformulathatconsistsofasinglerelationsymboland
i
nologicaloperators).TheresultofapplyingtheCQQ=q(x)totheinstanceIconsists
ofallthetuplesa(ofthesamelengthasx)suchthatq(a)istrueinI;wedenotethis
resultisdenotedbyQ(I).
2