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Service Matchmaking: Exploiting the Web
Transcript of Service Matchmaking: Exploiting the Web
Doctorate School of Sciences
Ph.D Program in Computer Science
Università degli studi di Milano - Bicocca
Supervisor: Prof. Flavio De Paoli
Tutor: Prof. Francesco Tisato
distributed software components
that provide functionalities
on the Web
Potentialities of Services
in order to develop
through the Web.
The research field
The research issues
Automation of Service Discovery
Automatic techniques for finding services that fulfill needs of service requesters
The literature proved that
is the most effective solution
for service discovery
List of matched services
It is able to
infer relations between concepts
that specifies service properties.
it manages homonyms and synonyms
between property values.
of reasoning is
Their main characteristic:
new wave of services
is growing on the Web:
of Web APIs are made available by several providers, including
Google, Facebook and Amazon
Providing public functionalities on the Web
Web API information is available on
Web API repositories
Heterogeneous Web Sources
Web API forums
Web API monitors
How users perform Web API discovery?
According to a survey that I performed, they use
Common Web search engines
perform ineffective service discovery
Why not Semantic Matchmaking?
according to a common model
(OWL-S, WSMO, etc.)
(HTML, XML, JSON, RSS, etc.)
Local description repository
Dispersed Web descriptions
Trustworthy and accurate
out-of-date or inaccurate
information from several
Semantic Web descriptions
such as: I/O parameters, operations, data formats, data licensing, ect.
Analysis of service properties
Properties can be:
operations, I/O parameters,
data licensing, response time,
operations, data licensing
price, response time
on the Web documents
such as provider popularity,
quality of documentation, etc.
The most relevant for users
To represent services, I propose
(Lightweight Policy-Centered Metamodel)
fb:dataFormat rdf:type pcm−lite:property . fb:dataFormat pcm−lite:hasValue dbpedia:JSON
fb:dataFormat pcm−lite: dbpedia:XML.
fb:userRating rdf:type pcm−lite:property .
fb:userRating pcm−lite:hasOp dbpedia:Greater_than
fb:userRating pcm−lite:hasValue "3"
fb:userRating pcm−lite:hasUnit dbpedia:Stars.
Novel characteristics of PCM-lite
Considering functional and non-functional properties at the same time
since categorization is subjective and/or domain dependent
that reduces reasoning response time
map portions of source documents that contains property values with the resulting policy
Named entity recognizer
"Data provided under
Creative Commons license"
identifies semantic concepts
in text portions
I considered three subjective properties:
Search volume of provider name on Google
Number of mashups that use the API on ProgrammableWeb
Number of daily active users on
Google Groups forums
Moreover, an experiment proved that
these properties are correlated
missing values can be estimated
Three quality metrics are evaluated
similarity score between the identified concept and the text context.
number of users that follow the source on social networks
The metrics are composed to provide an overall quality assessment
Description fusion is performed by using
that can be defined
manually by domain experts
automatically by ontology matching tools
One of three fusion functions can be associated with each mapping:
This matchmaking process is an extension of the approach proposed in [Palmonari et al., 2009]
The novel characteristic of this approach is exploiting the quality of the information provided
The overall approach is implemented by
(Policy Matchmaker and Ranker for Web)
RESTful distributed architecture
is able to
manage performance issues
due to reasoning and data crawling
500 descriptions from ProgrammableWeb, WebMashups and Wikipedia
1816 property values
718 property fusions
20 realistic requested policy
The component that
most affects precision and recall
named entity recognition
during the extraction phase
Test performed on 500 policies extracted
The execution time is acceptable with more than 6 Service matching endpoints
The main novel aspects of my PhD work are:
an approach for semantic matchmaking on non-semantic data
evaluation techniques for subjective properties of services
a scalable architecture that makes feasible matchmaking on Web data.
Techniques for automatic construction of S2PTs
A general approach for subjective properties
Application of the approach on human services (e.g., public transportation, mobile applications and tourist services)
 L. Panziera, M. Comerio, M. Palmonari, F. De Paoli, and C. Batini.
Quality-driven Extraction, Fusion and Matchmaking of Semantic Web API Descriptions.
Journal of Web Engineering, 11 (3), 247-268, Rinton Press 2012.
 L. Panziera, M. Comerio, M. Palmonari, and F. De Paoli.
Distributed matchmaking and ranking of web apis exploiting descriptions from web sources
. In Proc. of IEEE International Conference on Service-Oriented Computing and Applications (SOCA), pages 1-8, IEEE, 12-14 Dec. 2011
 L. Panziera, M. Comerio, M. Palmonari, C. Batini, and F. De Paoli.
PoliMaR- Web: multi-source semantic matchmaking of Web APIs.
In Proc. of 13th International Conference on Web Information Systems Engineering (WISE), pages 812–814, LNCS, Springer, 2012.
 M. Comerio, F. De Paoli, M. Palmonari, and L. Panziera.
Web service contracts: Specification and matchmaking
. Advanced Web Services, Springer, 2013, to apper.
 L. Panziera and F. De Paoli.
A Framework for Self-descriptive RESTful Services
. In Proc. of Fourth International Workshop on RESTful Design (WS-REST 2013) at the IW3C2 WWW 2013 Conference, pages 1407-1414, May 13–17, 2013, Rio de Janeiro, Brazil.
 L. Panziera, M. Palmonari, M. Comerio, and F. De Paoli.
WSML or OWL? A lesson learned by addressing NFP-based selection of semantic Web services
. In Proc. of NFPSLAM-SOC workshop, LNCS, Springer, 2010.
 Hong-Linh Truong, Marco Comerio, Andrea Maurino, Schahram Dustdar, Flavio De Paoli, and Luca Panziera.
On Identifying and Reducing Irrelevant Information in Service Composition and Execution
In of 11th International Conference on Web Information Systems Engineering (WISE), pages 812–814, LNCS, Springer, 2010.
 A. Carenini, D. Cerizza, M. Comerio, E. Della Valle, F. De Paoli, M. Palmonari, L. Panziera, and A. Turati.
A solution to the logistics management scenario with the glue2 web service discovery engine
. Semantic Web Services: Advancement Through Evaluation, Springer, 2012
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is exploited for subjective property evaluation
A working demo is available online
Social media analysis