In the field of Semantic Web Services, the automatic composition of services has been a challenging research problem. At the same time, mainly due to increasing number of available services and their heterogeneity, the industry has demanded for techniques that automate the process of selection and composition of services. Thus, several techniques for semantic service composition have been developed, but these techniques have shown to considerably hinder the overall performance of the application, making their use very expensive. One of the factors that contribute to this performance problem is the way that planners check the similarity between the ontologies concepts, i.e. the Concepts Matching. Thus, the choice of a proper technique for Concepts Matching directly influences the overall performance of the system and the choice of a proper technique is considered a key design decision in semantic web services. In this context, we propose the use of a Concepts Matching technique based on a Synonyms Dictionary approach aiming to reduce the performance issues found in service composition process. To validate our proposal, we present a systematic experimental analysis which compares this technique with other two approaches. The results show that the Synonyms Dictionary technique has the best performance when compared to other techniques.

1. A Synonyms Dictionary approach in
Semantic Web Services Composition
Heitor Barros
Co-authors: Tarsis Marinho, Evandro Costa, Jonathas Magalhães and Patrick Brito

2. Semantic Web Services
Web
Service
Describes
Semantic
Description

3. Semantic Web Services
Web
Service
Describes
Ontologies
Semantic
Description

4. Semantic Web Services
Web
Service
Describes
Semantic
Description
Uses
Service
Discovery
Technique

5. Semantic Web Services
Web
Service
Invokes
Select a
Service
Describes
Semantic
Description
Service
Execution
Engine
Uses
Service
Discovery
Technique

6. Semantic Web Services
Web
Service
Invokes
Select a
Service
Describes
Semantic
Description
Service
Execution
Engine
Uses
Uses
Service
Discovery
Technique
Composition
Planner

7. Semantic Web Services
Web
Service
Invokes
Service
Execution
Engine
Invokes
Service Composition
Select a
Service
Describes
Semantic
Description
Uses
Uses
Service
Discovery
Technique
Composition
Planner
Plans

8. Semantic Web Services
Web
Service
Invokes
Service
Execution
Engine
Invokes
Service Composition
Select a
Service
Describes
Semantic
Description
Uses
Uses
Service
Discovery
Technique
Composition
Planner
Plans

9. SWS Composition
Example:

10. Concepts Matching
A Concepts Matching technique checks if two concepts are
similar.
In Discovery Process, it checks if service description
matches the discovery request.
● Inputs and Outputs parameters, preconditions,
effects, service category, etc.

11. Concepts Matching
In Composition Process, the Concepts Matching technique also is used
to analyze the relationship between services.

12. Research Problem
Problem: poor performance in the composition process.
Mokhtar et al. (2007), Klusch and Gerber (2006) and
Talantikite et al. (2009).
Research Question: How to improve the performance of
Composition Process?

13. Our Proposal
The Concepts Matching technique affects on
the performance of services composition.
So, we propose a synonyms dictionary
technique to improve the composition process.

14. Synonyms Dictionary
This technique uses a dictionary structure to
keep the information about the concepts
similarity.
● For each Concept in the Dictionary there
is a set of related concepts that are similar
to him.

15. Synonyms Dictionary
Dictionary Example:

16. Evaluation
Goals
● Check the effectiveness of the proposed technique.
● Compare the composition process using the Synonyms
Dictionary with other Concepts Matching techniques.

17. Evaluation
We chose the following techniques:
● Semantic Matching (Paolucci et al., 2002).
● Cosine Similarity Measure (Klusch, 2006).
● Synonyms Dictionary.

18. Evaluation
We chose the following techniques:
● Semantic Matching (Paolucci et al., 2002).
● Cosine Similarity Measure (Klusch, 2006).
● Synonyms Dictionary.
○ The dictionary was built using the Semantic
Matching technique.

19. Evaluation
We utilized the OWLS-TC v4 services.
● semwebcentral.org/projects/owls-tc/.
This base has 1083 Semantic Web services written in
OWLS 1.1 in 9 different domains (Education, Medicine,
Food, Travels, Communications, Economy, Weapons,
Geography and Simulation).

20. Evaluation
● We use Grinv Middleware
to make the Composition
Process.
● Grinv allowed us to
customize the composition
techniques (Barros, 2011).
More about Grinv at:
github.com/HeitorBarros/Grinv

21. Evaluation
We have developed three versions of a
backward chaining algorithm for composition
planning.
Each version has
Matching technique.
a
different
Concepts

22. Evaluation
Composition Scenario:

23. Evaluation
Composition Scenario:
● There was only one correct composition.
● Every technique was able to find the
correct composition.
We are evaluating performance, not quality.

24. Evaluation
Composition Scenario:
1.
2.
3.
Repository with 100 Services.
Repository with 600 Services.
Repository with 1000 Services.
For each of these scenarios were performed 10 repetitions.

25. Results

26. Results

27. Results

28. Results

29. Conclusion
The experiment shown that the planning of compositions
using Synonyms Dictionary had the lowest response time.
The use of Synonyms Dictionary is efficient in automatic
composition of services.
The Concepts Matching technique affects on the
performance of services composition.

30. Future Work
Improve Quality:
● We will design the integration of other
Concepts Matching techniques with the
Dictionary in order to improve the quality of
relationships in the dictionary and enable the
integration of new ontologies at run time.

31. References
❏
❏
❏
❏
Mokhtar, S. B., Preuveneers, D., Georgantas, N., Issarny, V., & Berbers, Y. (2007). EASY:
Ecient SemAntic Service DiscoverY in Pervasive Computing Environments with QoS and
Context Support. Journal of Systems and Software, 81(5), 785–808.
Klusch, M., & Gerber, A. (2006). Evaluation of Service Composition Planning with OWLS-XPlan.
In Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and
Intelligent Agent Technology (pp. 117–120). Washington, DC, USA: IEEE Computer Society.
Retrieved from http://dx.doi.org/10.1109/WI-IATW.2006.68 doi: 10.1109/WI-IATW.2006.68.
Talantikite, H. N., Aissani, D., & Boudjlida, N. (2009, November). Semantic annotations for web
services discovery and composition. Comput. Stand. Interfaces, 31, 1108–1117. Retrieved from
http://dl.acm.org/citation.cfm?id=1595894.1596056 doi: 10.1016/j.csi.2008.09.041
Paolucci, M., Kawamura, T., Payne, T. R., & Sycara, K. (2002). Semantic Matching of Web
Services Capabilities. The Semantic Web - ISWC 2002: First International Semantic Web
Conference, Sardinia, Italy, June 9-12, 2002. Proceedings, 333+.

32. References
❏
❏
Klusch, M., Fries, B., & Sycara, K. (2006). Automated semantic web service discovery with
OWLS-MX. In AAMAS ’06: Proceedings of the fifth international joint conference on Autonomous
agents and multiagent systems (pp. 915–922). New York, NY, USA: ACM. doi: 10.1145
/1160633.1160796
Heitor Barros, Alan Silva, Evandro Costa, Ig Ibert Bittencourt, Olavo Holanda, Leandro Sales
(2011), Steps, techniques, and technologies for the development of intelligent applications
based on Semantic Web Services: A case study in e-learning systems, Engineering Applications
of Artificial Intelligence, Volume 24, Issue 8, December 2011, Pages 1355-1367, ISSN 09521976, http://dx.doi.org/10.1016/j.engappai.2011.05.007.

33. Thank you!
Contact: heitor.barros@copin.ufcg.edu.br