Cardoso J. "Semantic Web: Theory, Tools and Applications"
Semantic Web Service Discovery:
Methods, Algorithms and Tools
Chapter 11
Do not put anything here.
This area is reserved
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Cardoso J. "Semantic Web: Theory, Tools and Applications"
2
Chapter Outline
Introduction
Web Services
Semantic Web Services
Web Service Discovery
Semantic Web Service Discovery
Architectures
Methods/algorithms
Tools
Open Issues
Cardoso J. "Semantic Web: Theory, Tools and Applications"
3
Web Services (WS)
programmatic interfaces for applications (i.e.,
business logic), available over the WWW
infrastructure and developed with XML
technologies
.
Cardoso J. "Semantic Web: Theory, Tools and Applications"
4
Semantic Web Services (SWS) I
Semantic Web (SW)
[
Antoniou, 2004]
Ontologies
Rules
Languages (e.g., OWL, RDF)
SW + WS = SWS
Web services annotated with semantics
Annotation includes:
Service description, provider details, service
operations, service execution model, service
parameters, service data flow, service
invocation details, …
Cardoso J. "Semantic Web: Theory, Tools and Applications"
5
Semantic Web Services II
The annotation terms adhere to
formal terminologies, a.k.a.
ontologies
Service
-
related SW technologies
DAML
-
S, OWL
-
S, WSDL
-
S, SWSO/SWSL,
WSMO/WSML
[Cardoso, 2005]
Cardoso J. "Semantic Web: Theory, Tools and Applications"
6
Chapter Outline
Introduction
Web Services
Semantic Web Services
Web Service Discovery
Semantic Web Service Discovery
Architectures
Methods/algorithms
Tools
Open Issues
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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WS Reference Architecture
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Architectural Components
Service Registry
“yellow pages” for services
Matching Algorithm
Implemented in Matching Engine
Affects discovery effectiveness
Service Request
Captures requestor’s
information need
Service Advertisement
Describes a service
Created by service provider
Assumption
:
Identical
format
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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WS Description
WSDL
XML language for textual service
description
UDDI
Data model and API for service
publication/searching
Contains links to WSDL documents
Main elements:
businessEntity, businessService,
bindingTemplate, tModel
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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WS Matchmaking
Standard UDDI
Keyword
-
and category
-
based search
“Find qualifiers” (e.g., wildcards)
Manual (Web browsing) or through API
Information Retrieval (IR) techniques
similarity measures, clustering, etc.
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Pitfalls of WS Discovery (1)
Informal description of service
functionality/capabilities
Unstructured, natural language descriptions
NAICS: Category
“
Dating Services
”
does not match
“
Personal Relationships Services
”
Incomplete description of service
functionality/capabilities
Providers are not obliged to provide complete service
info
Syntactic relevance vs. intentional relevance
Linguistic polysemy and ambiguity are problems
Keywords cannot capture operational service
semantics, useful during discovery/composition
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Pitfalls of WS Discovery (2)
Lack of constraint specifications
Preconditions and other constraints are
useful for the entire service lifecycle
Limited expressiveness of domain
classification schemes
E.g.,
NAICS
,
UNSPSC
No support for indirect matching
UDDI does not support even simple
compositions
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Chapter Outline
Introduction
Web Services
Semantic Web Services
Web Service Discovery
Semantic Web Service Discovery
Architectures
Methods/algorithms
Tools
Open Issues
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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New Architectural Components (1)
Service Annotation Ontologies (SAO)
Formal service description models
Specify service capabilities
OWL
-
S, WSMO, WSDL
-
S, SWSO
Domain Ontologies
Domain
-
specific terminologies
Substitute keywords and free text in service
descriptions
Hierarchies of concepts and relationships
Written in OWL, DAML+OIL, RDF(S), …
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Example: The OWL
-
S SAO
Service Profile
[
Martin, 2005]
Human
-
readable service description and
provider’s contact details
Functional parameters
Inputs, Outputs, Preconditions, Effects
Non
-
functional parameters (e.g., QoS)
Mostly used in service discovery
Service Model
Control and data flow of service execution
Service Grounding
Service access and invocation details
Link to WSDL description
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Example: A Beer domain ontology
http://www.dayf.de/2004/owl/beer_v0.3.owl
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Revised “Traditional” Components
Service Registry
UDDI is still used but with references to semantic
descriptions
Matching Algorithm
More complex and “intelligent”
Exploits the formal semantics of service descriptions
Service Advertisement
Written in a SAO
Refers to concepts of a domain ontology
Service Request
Usually similar to an advertisement
Ontology integration and semantic mediation can be
applied to bridge different request
-
advertisement
specifications
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Centralized Architecture I
Semantic extension of UDDI
tModels point to semantic
descriptions
Translator creates such
semantic tModels
Semantic matching is
performed in an external
engine
Keyword
-
based matching can
still be used
Some extensions to UDDI
Inquiry API are needed
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Centralized Architecture II
The matching algorithms
themselves are published as WS
Support for diverse SAOs and
matching algorithms
Step1:
Ad hoc
selection of the
best matching service
Step2: Invocation of selected
service with the request as
parameter
Requires minor UDDI API changes
Allows more flexible business
models but complicates service
composition
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Peer
-
to
-
Peer Architecture
P2P suitable (i.e., scalable, efficient) for distributed environments (e.g.,
Web)
Peers may be service requestors or providers
Each peer
-
requestor
may use its own
matching algorithm
Each peer
-
provider
can directly update
the local service
advertisements
Result: high flexibility
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Chapter Outline
Introduction
Web Services
Semantic Web Services
Web Service Discovery
Semantic Web Service Discovery
Architectures
Methods/algorithms
Tools
Open Issues
Cardoso J. "Semantic Web: Theory, Tools and Applications"
22
Degree of Match (DoM)
A
value that expresses how similar
two entities are, with respect to some
similarity metric(s)
Important feature of most SWS
matchmaking approaches
Allows for ranking of discovered
services
Example DoM set: exact, plugin,
subsumes, subsumed
-
by, fail
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Variety of Matchmaking Approaches
Direct
Return only single services that match the
request
Indirect
Compute service compositions (or “chains” in
the simplest case)
Logic
-
based
Description Logics and First Order Logic
reasoning
Similarity
-
based (IR techniques)
Linguistic similarity, term frequency, …
Graph matching
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Approach I
–
Semantic Capabilities
Matching
A pioneering work
[Paolucci, 2002a]
Main idea
An advertisement A matches a request R when all the
outputs of R are matched by the outputs of A, and all
the inputs of A are matched by the inputs of R
DL subsumption matching between inputs and outputs
Outputs
are regarded more significant than
inputs
Degree of Match
Matching conditions
EXACT
If req.o is
equivalent
to adv.o, or
If req.o is a direct subclass of adv.o
PLUGIN
If adv.o
subsumes
req.o
SUBSUMES
If req.o
subsumes
adv.o
FAIL
If there is no subsumption relationship between
req.o and adv.o
The
inverse
conditions
hold for
inputs
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Approach II
–
Multi
-
level Matching
A variant of Approach I
Main idea
Both functional and non
-
functional service data
matters
Multi
-
level matching
IOPE attributes, service categories, custom
service parameters (e.g., QoS
-
related)
DoM aggregation
Weighting the DoM of the various levels
A very difficult optimization problem
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Approach III
–
DL Matchmaking
with Service Profile Ontologies
Service Profile Ontology
Concepts are DL expressions of service
constraints
DL reasoners create the ontology tree
A logic
-
based service registry
DL subsumption matching
The DoM set of Approach I is re
-
defined
A new DoM is introduced
[Li, 2004]
An advertisement matches a request if
their intersection is satisfiable
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Approach III
-
Example
2 Advertisements
and a Request Q
The Service Profile Ontology after DL reasoning
DoM(Q,FreeDatingService) =
PLUGIN
DoM(Q,FreeDatingServiceForMovie…) =
SUBSUME
*Assumption: PLUGIN is better than SUBSUME
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Approach IV
–
Similarity Measures and
Information Retrieval Techniques
Pure Logic
-
based matching may have
counterintuitive results. Example:
R input: InterestProfile
⊓
hasInterest.SciFiMovies
R output: ContactProfile
A input: InterestProfile
A output:
ChatID
DoM(R,A) =
FAIL
Reason: output of R is
disjoint with
output of A
although their inputs are
“logically relevant”
PersonalProfile
InterestProfile
ChatID
ContactProfile
is
-
a
disjoint
-
with
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Approach IV
–
Similarity Measures and
Information Retrieval Techniques
Solution
–
Main idea
Allow for more “flexible” methods of assessing
service similarity
IR and similarity
-
based methods are perfect
candidates
E.g., linguistic semantics (WordNet similarity),
TF
-
IDF
Logic is just one component of
“relevance”
Such methods capture some other components
A problem remains
How much should each method contribute to the
DoM calculation
An optimization problem
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Approach V
–
A Graph
-
based Approach
A service is represented as a DAG
Nodes ~ individuals of concepts
Arcs ~ roles between individuals
Main idea
Structural match
:
Two service descriptions match if they have the
same structure and the corresponding nodes match
Existing graph matching algorithms apply
No (obvious) support for DoM
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Approach VI
–
Indirect Graph
-
based Matching
Indirect matching
Complex workflow compositions
“Service chains” in the simplest case
Service chain creation rules
1) The inputs of each involved service match
either the request inputs or the outputs of
the previous service in the chain.
2) Each output of the request is matched
against an output of the last service in the
chain.
Cardoso J. "Semantic Web: Theory, Tools and Applications"
32
Approach VI
-
Example
Service
Inputs
Outputs
S1
A, B
E
S2
A, B, C
F, N
S3
E, C
F
S4
F
K, M
S5
K, D
Z, Y
S6
K
D, Z
S7
D
Y
Discovered Service
Chains
S1, S3, S4, S6, S7
S1, S3, S4, S5
S2, S4, S6, S7
S2, S4, S5
Request inputs:{A,B,C,D}
Request outputs:{Z,Y}
3:
1: Service
specifications
2: Service
graph
Policy
-
based
service chain
selection can be applied
(e.g., the shortest)
S1
S2
S3
S4
S5
S6
S7
Cardoso J. "Semantic Web: Theory, Tools and Applications"
33
Approach VII
–
Indirect Backward
Chaining Matching
A similar approach for discovery of complex
service workflows… but implemented
through logic resolution
Main idea:
backward
-
chaining
goal
-
driven reasoning procedure
starting from services that match the request
outputs (but not its inputs), we recursively try to
link them with other services until we find a
service with all its inputs matched to the inputs
given by the request
Inherent support by logic programming
tools (Prolog)
Cardoso J. "Semantic Web: Theory, Tools and Applications"
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Synopsis of Approaches
Characteristics
Approach
Matching elements
Support for DoM
Indirect matching
Algorithm
I
IO
Yes
No
Logic
II
IO, service category,
custom parameters
Yes
No
Logic
III
Service profile
Yes
No
Logic
IV
Textual descriptions,
IOPE
Yes
No
Logic+
Similarity
V
Service profile
No
No
Logic+
graphs
VI
IO
No
Yes
Hybrid+
graphs
VII
IO
No
Yes
Logic
Cardoso J. "Semantic Web: Theory, Tools and Applications"
35
Chapter Outline
Introduction
Web Services
Semantic Web Services
Web Service Discovery
Semantic Web Service Discovery
Architectures
Methods/algorithms
Tools
Open Issues
Cardoso J. "Semantic Web: Theory, Tools and Applications"
36
OWL
-
S/UDDI Matchmaker
(OWL
-
S/UDDIM)
OWL
-
S services
OWL domain ontologies
DL subsumption
-
based matchmaking
Standalone and Web
-
based versions
Standalone version has a client API
Open source (Java)
Intelligent Software Agents Group
,
Carnegie Mellon University
http://projects.semwebcentral.org/projects
/owl
-
s
-
uddi
-
mm/
Cardoso J. "Semantic Web: Theory, Tools and Applications"
37
IBM Semantic Tools for Web
Services (STWS)
WSDL
-
S services
OWL domain ontologies
Applies AI planning techniques to find
composite services that match the
request
Eclipse plug
-
in
Exploits the WordNet lexicon
http://www.alphaworks.ibm.com/tech
/wssem
Cardoso J. "Semantic Web: Theory, Tools and Applications"
38
Hybrid OWL
-
S Web Service
Matchmaker (OWLS
-
MX)
OWL
-
S services
OWL domain ontologies
Logic
-
based matching + syntactic token
-
based similarity metrics
A service test collection is also available
Open source (Java)
German Research Center for Artificial
Intelligence, DFKI Saarbruecken
http://www.dfki.de/~klusch/owls
-
mx/
Cardoso J. "Semantic Web: Theory, Tools and Applications"
39
METEOR
-
S Web Service Discovery
Infrastructure (MWSDI)
-
Lumina
WSDL
-
S services
OWL domain ontologies
Adds semantic to the whole service lifecycle
METEOR
-
S discovery API used by the
graphical tool Lumina (Eclipse plug
-
in)
Open source (Java)
Large Scale Distributed Information
Systems (LSDIS) Lab, University of Georgia
http://lsdis.cs.uga.edu/projects/meteor
-
s/illumina/
Cardoso J. "Semantic Web: Theory, Tools and Applications"
40
TUB OWL
-
S Matcher (OWLSM)
OWL
-
S services
OWL domain ontologies
DL subsumption
-
based weighted matching
over many service parameters
Open source (Java)
Technical University of Berlin
http://kbs.cs.tu
-
berlin.de/ivs/Projekte/owlsmatcher/index.ht
ml
Cardoso J. "Semantic Web: Theory, Tools and Applications"
41
WSMX Discovery Component
WSMO services
WSML domain ontologies
Part of the WSMO reference
implementation
Open source (Java)
WSMX working group, European
Semantic Systems cluster initiative
http://www.wsmx.org/
Cardoso J. "Semantic Web: Theory, Tools and Applications"
42
Chapter Outline
Introduction
Web Services
Semantic Web Services
Web Service Discovery
Semantic Web Service Discovery
Architectures
Methods/algorithms
Tools
Open Issues
Cardoso J. "Semantic Web: Theory, Tools and Applications"
43
Evaluation of Discovery
Evaluation of efficiency (e.g., scalability,
service retrieval times) is not enough
Retrieval effectiveness must be assessed
Several obstacles exist
Lack of SWS test sets and evaluation testbeds
OWL
-
S Test Collection (TC) is a good start
[Klusch, 2005]
Lack of appropriate evaluation metrics
Standard IR metrics (precision, recall) may not
apply as
-
is
Cardoso J. "Semantic Web: Theory, Tools and Applications"
44
Semantic Interoperability/Mediation
In practice, service requestors and service
providers will use different SAO and/or
domain ontologies
A mediation layer will be necessary
Provision of ontology matching and alignment
Translation from natural language requests to
formal ontology
-
based
WSMO discovery heavily relies on
mediators
[
Roman, 2005]
Cardoso J. "Semantic Web: Theory, Tools and Applications"
45
Maturity of Discovery Tools/Engines
Tools are not limited to discovery
frameworks, but also include:
Registries
Annotation tools
Service editors
No stable, fully
-
documented tools
currently exist
Interoperability between research
efforts is a major issue
Cardoso J. "Semantic Web: Theory, Tools and Applications"
46
Fuzziness in Discovery
Soft Computing concepts may give added
value to SWS discovery through
approximate matching
Human information needs may not be
completely represented by ontologies which
are rather crisp KR tools
Even reasoning over concrete domains may
be insufficient in practice
Researchers are already pursue
fuzzification of ontologies and matchmaking
Cardoso J. "Semantic Web: Theory, Tools and Applications"
47
Conclusion
SWS provide new opportunities for
effective service discovery
Most existing solutions exploit DL
reasoning services
IR and knowledge discovery techniques
seem to be applicable
There are interesting tools but only at a
research
-
level
However, many open issues still exist
Cardoso J. "Semantic Web: Theory, Tools and Applications"
48
Conclusion
See
Appendix I
for a mini
-
tutorial
on a SWS discovery tool
See
Appendix II
for a DL primer
p
-
comp web site
http://p
-
comp.di.uoa.gr
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