querying knowledge graphs by example en;ty...

UsabilityChallenges

QueryingKnowledgeGraphsbyExampleEn;tyTuplesNandishJayaram1+,ArijitKhan2*,ChengkaiLi1,XifengYan2,RamezElmasri1

UniversityofTexasatArlington1 UniversityofCalifornia,SantaBarbara2

RelatedWork

N.Jayaram,A.Khan,C.Li,X.YanandR.Elmasri.QueryingknowledgegraphsbyexampleenOtytuples,TKDE2015.N.Jayaram,M.Gupta,A.Khan,C.Li,X.YanandR.Elmasri.GQBE: Querying knowledge graphs by example enOty tuples,ICDE2014.DemoURL:hXp://idir.uta.edu/gqbe

TechnicalDetailsandDemo

QueryProcessing

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Query

GQBE NESS Baseline

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q Bigandcomplexdata:Lackofschema,challengingtousersanddevelopers.

q Howtoquerythegraph,andunderstandtheresults.

q Query-by-exampleinrelaOonaldatabases[Zloof’75].q Keyword search and keyword-based queryformulaOon[Changetal.’11].

q Set expansion [Wang et al.’07]. XML queryrelaxaOon[Amer-Yahiaetal.’2005].

q Exemplarqueries[Moinetal.,2014].

QueryInterface

Experiments

QueryGraphDiscovery

AnswerSpaceModeling

Mul;-TupleQueryGraphs

q Nodes(F)and(HL)aretwominimalquerytrees.q Node (F) corresponds to the sub-graph thatconnects Jerry Yang and Yahoo through edgefounded.

q Node (FGHLP) is theMQG, and it correspondstotheenOrequerygraphonthelem.

GroundtruthbasedaccuracycomparisonofGQBEandNESS.ComparisonofGQBE,NESSandExemplarQueries.Themeasuredparametersareprecision-at-k,MeanAveragePrecisionandnormalizedDiscountedCumula;veGain.

Pearson Correla;on Coefficient (PCC) between GQBE and AmazonMechanicalTurkWorkers, fork=30.MTurkworkerswerepresentedwithanswerpairsandaskedfortheirpreferencebetweenthetwoanswers ineachpair.20000suchopinionscollected.

Queryprocessing;mesofGQBE,NESSandBaseline.

Obtain neighborhoodgraph.

Weight edges usingheurisOcs and use agreedy approach too b t a i n a s m a l l e rconnectedMQG.

A l l the super -graphs of a nullnodearepruned.

(GHL), a node that does not haveanyanswers,isanullnode.

Ini;alLaXce

Lower Bound (LB): edgematching score of thecorrespondinggraph.

Upper Bound (UB): scoreof the highest-scoredsuper-graphinthelaice.

GQBEArchitecture

MulOple MQGs are mergedbased on edge labels andvertexlabelmatches.

Modified laXce withrecomputed upperboundary

KnowledgeGraphs

Input:anexampleofwhattheuserwantstofind.

AccuracyofGQBEonmul;-tuplequeries,k=25.

LaXcenodesevaluatedcomparison.

Queryprocessing;mefor2-tuplequeries.

ParOallyfundedby:+NowwithPivotal,*NowwithNanyangTechnologicalUniversity,Singapore

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DATASETS:Freebase(28Mnodes,47Medges,5400relaOonships)DBpedia(759Knodes,2.6Medges,9100relaOonships)QUERIES:20QueriesonFreebase8QueriesonDBpedia

Q u e r yGraph1

Q u e r yGraph2