Service discovery with semantic alignment
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Service discovery with semantic alignment Alberto Fernández AT COST WG1 meeting, Cyprus, 15-16 Dec, 2009
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Service discovery with semantic alignment. Alberto Fernández AT COST WG1 meeting, Cyprus, 15-16 Dec, 2009. Introduction. Service coordination in open environments Identification of functionality (service) required Service provider discovery - PowerPoint PPT Presentation
Transcript of Service discovery with semantic alignment
Service discovery with semantic alignment
Alberto Fernández
AT COST WG1 meeting, Cyprus, 15-16 Dec, 2009
Introduction Service coordination in open environments
Identification of functionality (service) required Service provider discovery Service provider selection (trust, reputation, QoS) Service engagement (negotiation) Service invocation
Agreement Technologies for Service coordination Semantics, negotiation, trust, …
Service Provider Discovery Matching service advertisements against
service requests Service description languages Usually identical for advertisements and
request
OWL-S service profile example
INPUTS
OUTPUTS
CATEGORIES
PARAMETERS
EFFECTS/PRECONDITIONS
Ontology
Service Provider Discovery Semantic Mismatches
Service description models Domain ontologies
Architecture
servicedescription
servicerequest
Model Alignment
servicedescription
servicerequest
Service Matching
Degree of
match
dom(C1,C2)
LocalAlignment
KB
LocalAlignment
KB
ServiceDirectoryService
Directory
SemanticConceptMatching
ConceptAlignment
AlignmentRegistry
AlignmentRegistry
Different ontologies
OWLS, WSMO, SAWSDL, WSDL, keywords, text,…
Service Model Alignment Service Description Approaches
Semantic: OWL-S, WSMO Syntactic: WSDL Hybrid: SAWSDL Light models: keywords, tag-clouds, textual
Common models for pairs of SD models Possible loss of expressiveness
Integrated model for service discovery Union of common models
Integrated model for service matchmaking
Integrated model for service matchmaking
Element OWL-S WSMO SAWSDL WSDL Keyword(tag)
TagCloud Text
input x x x x - - -
output x x x x - - -
precondition x x - - - - -
effect x x - - - - -
keywords - - - - x - -
text x x - - - - x
category x x x - - - -
tag cloud - - - - - x -
Integrated model for service matchmaking
Element OWL-S WSMO SAWSDL WSDL Keyword(tag)
TagCloud Text
input x x x x - - -
output x x x x - - -
precondition x x - - - - -
effect x x - - - - -
keywords Osem Osem Osem Osyn x Osyn Osyn
text x x Osem Osyn Osyn Osyn x
category x x x Osyn - - -
tag cloud Osem Osem Osem Osyn Osyn x Osyn
Architecture
servicedescription
servicerequest
Model Alignment
servicedescription
servicerequest
Service Matching
Degree of
match
dom(C1,C2)
LocalAlignment
KB
LocalAlignment
KB
ServiceDirectoryService
Directory
SemanticConceptMatching
ConceptAlignment
AlignmentRegistry
AlignmentRegistry
Service Matching Aggregation over matching of individual
concepts (only for common fields) Current approaches to Semantic IOPE
IAIR
OROA
PAPR
EREA
Semantic Concept Matching Degree of Match between CA and CR. Combination of
Level of Match subsumption relation Exact, plugin, subsumes, fail, …
Concept Similarity Semantic distance
Semantic Concept Matching
vehicle
carvan truck bus
Japanesecar
hondamazda nissan toyota
Americancar
chevy dodge ford
searched
found
plug-inlevels
of match
Semantic Concept Matching
vehicle
carvan truck bus
Japanesecar
hondamazda nissan toyota
Americancar
chevy dodge ford
found
searched
subsumes levels of match
exact > plug-in > subsumes > fail
Semantic Concept Matching
vehicle
carvan truck bus
Japanesecar
hondamazda nissan toyota
Americancar
chevy dodge ford
distance = 2 conceptsimilarity
Service Matching Non IOPEs (keywords, tag clouds, categories)
Syntactic:
Semantic:
QS
QSSQsim
),(
Ss
Ss
s
s
q
qSQsim ),(
)...),(),,(),...,,(),,(( 2121 sqsimsqsimqqsimqqsimq
Concept Alignment Alignments (or mappings) between two
ontologies O and O’:
<e, e’, n, R> where: e and e’ are the entities considered n: is a degree of trust (confidence) R is the relation holding between e and e’.
Representation in RDF SPARQL for querying
Open Issues SPARQL as query language Two stage discovery process
e.g. the requester doesn't know the inputs required Matchmaking completely in the directory?
Private information Scalability
Distributed directories Ontology alignments discovery
Conclusions Summary
Architecture for service discovery Semantic alignment Common model for service descriptions
Future work Implementation (currently) and evaluation Open issues pointed out
Service discovery with semantic alignment
Alberto Fernández
AT COST WG1 meeting, Cyprus, 15-16 Dec, 2009
