Authors: An-Ping Zhao; Lei Yu; Wei-Ming Yang
Addresses: College of Computer and Information Science, Chongqing Normal University, Shapingba, Chongqing 401331, China ' College of Computer and Information Science, Chongqing Normal University, Shapingba, Chongqing 401331, China ' College of Computer and Information Science, Chongqing Normal University, Shapingba, Chongqing 401331, China
Abstract: As a key enabler to achieve the full potential of service computing, service community discovery is employed to support web service intelligent application effectively. The proposed framework applies a semantically structured approach to the web service community modelling for service community discovery based on probabilistic graphical model and probabilistic topic model. The approach to the problem is to identify web services of a service community based on both the semantics of the functional properties of web services and the graph structure of the inherent semantic association, dependency among services, which not only leverages the semantic functionality property but also exploits the semantic association relationship between services and operations. The experimental results and analysis shows that the proposed approach is efficient, feasible and practical. The result of the present work implied that the service community can be discovered by the approach and also has the full semantic interpretation.
Keywords: semantics; semantic relationships; probabilistic topic models; probabilistic graph models; service communities; community discovery; functionality; web services; modelling; semantic association; service dependency; services; operations.
International Journal of Computational Science and Engineering, 2016 Vol.13 No.3, pp.233 - 245
Received: 15 Feb 2014
Accepted: 27 May 2014
Published online: 24 Aug 2016 *