An approach for semantic web services automatic discovery and composition with similarity metrics

ABSTRACT

With the emerging growth of web services tecnology, the Web is now evolving to become a service provider. In this context, the semantic web services discovery and composition are hard tasks because injecting context into adaptive service integration raises a number of significant challenges, i.e. defining effective metrics to manage adaptation. This paper proposes an algorithm for Semantic Web Services discovery and compositon which makes use of similarity metrics.

REFERENCES

• 1: R. D. Giv, B. Kalali, S. Zhang, N. Zhong, and A. Lopez-Ortiz. Algorithms for direct and indirect semantic matching of web services. Technical report, University of Waterloo, 2004.
• 2: Jiangang Ma , Yanchun Zhang , Jing He, Efficiently finding web services using a clustering semantic approach, Proceedings of the 2008 international workshop on Context enabled source and service selection, integration and adaptation: organized with the 17th International World Wide Web Conference (WWW 2008), p.1-8, April 22-22, 2008, Beijing, China [doi>10.1145/1361482.1361487]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.5 On-line Information Services
          Subjects: Web-based services

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Search process

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search
          Subjects: Plan execution, formation, and generation

General Terms:
Algorithms, Design, Experimentation

Keywords:
composition, discovery, semantic web services