Table Of ContentStudies in Computational Intelligence 453
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PolishAcademyofSciences
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Forfurthervolumes:
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Xia Wang and Wolfgang A. Halang
Discovery and Selection
of Semantic Web Services
ABC
Authors
Dr.XiaWang Prof.Dr.Dr.WolfgangA.Halang
GFaIe.V. LehrstuhlfürInformationstechnik
Berlin Fernuniversität
Hagen
ISSN1860-949X e-ISSN1860-9503
ISBN978-3-642-33937-0 e-ISBN978-3-642-33938-7
DOI10.1007/978-3-642-33938-7
SpringerHeidelbergNewYorkDordrechtLondon
LibraryofCongressControlNumber:2012948302
(cid:2)c Springer-VerlagBerlinHeidelberg2013
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To Xia’sparentsfortheirlove, understanding
andsupport
Abstract
The nextgenerationof web searchenginesnotonlypromisesto be able to search
for semantically related information dispersed over different web pages, but also
for semantic services which are functional entities performing certain tasks. This
functionality depends on the maturity of the technologies for the Semantic Web
(SW) and Semantic Web Service (SWS). With the development of the semantic
web and semantic web services, the discovery of semantic services becomes the
keyproblem.Toaddressit,thisbookpresentsasystematicmethodforwebservice
discoveryprovidingoptimalsearchresultsunderspecificuserservicerequirements.
Semantic web service discovery is, after all, a matchmaking process, which
semantically measures the similarity of a web service’s description with user
requirements.Sofar,servicediscoveryhasnotbeenaddressedclearlyandcompre-
hensively.The quality and results providedby currentapproachesare still incom-
plete and often erroneous, because either keyword searching or simple functional
matchmakingisused,only.Servicediscoveryisadifficultproblemnotonlydueto
its complexity, but also due to the limitations of pertaining research results avail-
able. Approaches borrowed from information retrieval, knowledge representation
and discovery,data mining, artificial intelligence, ontology engineering and com-
putinglogicsareconsideredtobeadaptedinordertosolvethisproblem.
Afteranextensiveanddetailedinvestigationofrelatedwork,thisbookidentifies
four problems not addressed by current solutions: (1) A clear web service model
suitableforselection islacking,becausethereistoo muchexcrescentinformation
interferingwiththeselectionprocessandimpairingitsoperationalefficiency,ifser-
vice selection is directly based on service descriptions. (2) No common domain
ontologiesexistforcertainkindsofwebservicesand,thus,serviceprovidersarein-
clinedtousetheirownserviceontologiesindescribingtheirservices.Theresulting
diversityofontologiespresentlyprevailingrendersdiscovery,selectionandinterop-
eration of servicesverydifficult, if notimpossible. (3)Withouta uniformdomain
ontologyservingasknowledgebase,thecurrentontology-basedservicediscovery
approach is very weak. It lacks rich semantic information to support matchmak-
ingofservices.(4)ServiceselectionbasedonQuality-of-Service(QoS)criteriais
currently not well developed and efficient. Syntactic measurement and evaluation
VIII Abstract
of all quality metrics of services are missing, rendering the discovery of services
impossible.
Addressingthesefourproblems,inthisbookthefollowingcontributionsarepre-
sented: (1) A novel service model is proposed, which is independentof semantic
service description models, and clearly defines all elements necessary for service
discoveryandselection.Suchaservicemodeltakesserviceselectionasitsgistand
improvesits efficiency.Correspondingselectionalgorithmsandtheir implementa-
tionascomponentsoftheeXtendedSemanticallyEnabledService-orientedArchi-
tecture(xSESA)intheWebServiceModelingEnvironment(WSMX)arepresented
indetail.(2)Ageneralapproachforbuildingapplicationontologiesispresented,of
whichmanyapplicationsofsemanticwebservices,e.g.discovery,compositionand
mediation,canbenefit.Withapplicationontologiesthusbuilt,servicediscoverycan
becarriedoutinthesamewayaswithsingledomainontologies,andthemediation
problembetweenserviceontologiesturnsouttobesolved.Then,anontology-based
approach to improve service discovery is proposed and thoroughly validated. (3)
Using the service model presented, a service selection approach oriented at QoS-
criteria is proposed. It normalises diverse qualities of a service in their respective
metricsandemploysaserviceselectionalgorithmbasedonsoundness.
A scalable experimental platform, named Web Services Application Ontology
(wsao) builder, has been developed to evaluate the work above. It systematically
demonstratesthe feasibility of the architectureproposedto discoversemantic ser-
vices.Experimentsrevealthatprecisionandrecallofserviceselectionbasedonap-
plication ontologies are significantly improved by about 15.1% and 14.7%,
respectively.
Acknowledgements. Dipl.-Ing.JuttaDu¨ring’scontributiontothisbookinformofdrawing
mostofthefigurescontainedishighlyappreciated.
Contents
Abstract........................................................... VII
Acronyms .........................................................XIII
1 Introduction................................................... 1
1.1 ProblemStatement ......................................... 2
1.2 ResearchQuestions......................................... 4
1.3 Contributions.............................................. 5
1.4 StructureofThisBook ...................................... 7
2 SemanticWebServicesandOntologies ........................... 9
2.1 WebServiceTechnologies ................................... 9
2.2 SemanticWebServices...................................... 13
2.2.1 SemanticWeb....................................... 14
2.2.2 SearchEnginesfortheSemanticWeb ................... 15
2.2.3 SPARQLasQueryLanguagefortheSemanticWeb ....... 16
2.2.4 SemanticallyEnabledWebServices .................... 17
2.3 SemanticAnnotationsforWSDLandXMLSchema ............. 20
2.4 SemanticWebServicesandOntologies ........................ 20
2.4.1 GenericWebServiceOntologies ....................... 21
2.4.2 WebServiceDomainOntologies ....................... 24
3 RelatedWork.................................................. 27
3.1 WhatIsWebServiceDiscovery?.............................. 27
3.2 MethodstoDiscoverWebServices............................ 29
3.3 MethodstoDiscoverSemanticWebServices ................... 30
3.4 MethodologytoBuildOntologies............................. 34
3.4.1 OntologyLearningMethodsandTools .................. 34
3.4.2 OntologyMerging ................................... 35
3.5 DiscoveryFrameworksforSemanticWebServices .............. 36
X Contents
4 AServiceModelFacilitatingtoDiscoverSemanticWebServices .... 39
4.1 ConceptualFrameworkforServiceDiscovery................... 39
4.1.1 Two-PhaseDiscovery................................. 40
4.1.2 Assumptions ........................................ 41
4.2 ServiceModelforDiscovery................................. 41
4.2.1 Definitions.......................................... 42
4.2.2 ServiceMatchmakingAlgorithms ...................... 49
4.2.3 ExamplesofMatchmakingAlgorithms.................. 56
4.3 ImplementationinWSMX................................... 56
4.3.1 TheExtendedSESA.................................. 56
4.3.2 DiscoveryComponent(DC) ........................... 58
4.3.3 SelectionComponent(SC) ............................ 59
4.4 AnE-GovernmentApplication ............................... 59
4.5 Summary ................................................. 60
5 BuildingApplicationOntologiesforSemanticWebServices......... 63
5.1 LevelsofOntologiesandRequirements........................ 63
5.2 ConceptualModelforApplicationOntologies .................. 64
5.2.1 DefinitionofOntologies .............................. 64
5.2.2 SemanticNetofOntologicalConcepts .................. 65
5.3 BuildingApplicationOntologies.............................. 66
5.3.1 ProcessofBuildingAO .............................. 67
5.3.2 WordNet-BasedConceptExtractionAlgorithm ........... 67
5.3.3 WordNet-BasedOntologyMergingAlgorithm............ 70
5.3.4 EliminatingConflictsbetweenOntologies ............... 74
5.4 ExperimentalPrototypes..................................... 75
5.5 Summary ................................................. 79
6 Ontology-BasedServiceSelection ................................ 81
6.1 Motivation ................................................ 81
6.2 Ontology-BasedSelectionFrameworkforSemanticWeb
Services .................................................. 83
6.3 OntologicalConceptsintheContextofSemanticWebServices.... 84
6.3.1 ConceptFeatures .................................... 84
6.3.2 ConceptDefinitioninWSMO.......................... 85
6.4 SemanticConceptSimilarity ................................. 85
6.4.1 SemanticNetwithMultipleConceptRelations ........... 86
6.4.2 SimilarityAlgorithmforFormalConcepts(OCSA)........ 87
6.4.3 SimilarityAlgorithmforCompositeConcepts ............ 89
6.5 SemanticServiceSimilarity.................................. 90
6.6 AlgorithmandExperimentalPrototype ........................ 90
6.6.1 DiscussionofExperimentalParameters.................. 93
6.7 Summary ................................................. 94
Contents XI
7 QoS-BasedSelectionofSemanticServices......................... 97
7.1 Motivation ................................................ 97
7.2 SimilarWorkandDiscussion................................. 98
7.3 QoSOntologyandVocabularyinWSMO ...................... 98
7.3.1 QoSOntologyandVocabulary ......................... 99
7.4 QoS-BasedSelectionofSemanticServices .....................101
7.4.1 QoS-BasedSelectionModes...........................102
7.4.2 CollectionofQoSMetrics.............................103
7.4.3 SelectionAlgorithm..................................104
7.5 ExperimentsandEvaluation..................................106
7.6 Summary .................................................107
8 Evaluation ....................................................109
8.1 EvaluationCriteria .........................................109
8.1.1 PrecisionandRecall..................................109
8.1.2 GoldenStandards....................................110
8.2 ExperimentalData..........................................111
8.2.1 CollectionofDataSets ...............................111
8.2.2 DataPreprocessing...................................113
8.3 ApplicationOntologyEvaluation .............................116
8.3.1 PerformanceofWordSenseDisambiguation .............116
8.3.2 PerformanceofMergingServiceOntologies .............118
8.4 EvaluationofSemanticServiceSimilarity......................120
8.4.1 PerformanceofServiceDiscovery......................120
8.4.2 PerformanceofDeterminingOntology-BasedService
Similarity...........................................122
8.5 Summary .................................................125
9 ConclusionandDirectionsforFutureResearch....................127
9.1 ConclusionandContributions ................................127
9.1.1 ServiceModeltoDiscoverSemanticWebServices........127
9.1.2 BuildingApplicationOntologies .......................128
9.1.3 Ontology-BasedServiceSelection......................129
9.1.4 QoS-BasedServiceSelection ..........................130
9.2 DirectionsforFutureResearch ...............................130
A DescriptionLogic,TBoxandABox...............................133
B PartofExperimentalData ......................................135
References.........................................................143
Acronyms
AI ArtificialIntelligence
AO ApplicationOntology
BPEL4WS BusinessProcessExecutionLanguageforWebServices
DAML DARPAAgentMark-upLanguage
DARPA DefenceAdvancedResearchProjectsAgency
DC DiscoveryComponent
DERI DigitalEnterpriseResearchInstitute
DL DescriptionLogic
FCA FormalConceptAnalysis
HTTP HyperTextTransferProtocol
IMsg InputMessage
IOPE Inputs,Outputs,Pre-conditionsandEffects
IRS InternetReasoningService
OIL OntologyInterchangeLanguage
OMsg OutputMessage
OWL WebOntologyLanguage
OWL-S WebOntologyLanguageforService
QoS QualityofService
RDF ResourceDescriptionFramework
RuleML RuleMark-upLanguage
SAWSDL SemanticAnnotationsforWSDL
SC SelectionComponent
SMTP SimpleMailTransferProtocol
SO ServiceOntology
SOAP SimpleObjectAccessProtocol
SP ServiceProvider
SR ServiceRequester
SW SemanticWeb
SWRL SemanticWebRuleLanguage
SWS SemanticWebService
