A self-learning framework for services selection

Authors:
H. Wang;Y. Wang;J. Z. Huang;X. Xu
Affiliations:
School of Computer Science and Engineering, Southeast University, Nanjing 210096, China.;School of Computer Science and Engineering, Southeast University, Nanjing 210096, China.;E-business Technology Institute, The University of Hong Kong, Hong Kong, China.;School of Computer Science and Engineering, Southeast University, Nanjing 210096, China
Venue:
International Journal of Information Technology and Management
Year:
2010

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Abstract

Service-Oriented Architecture (SOA) is emerging as a new paradigm for integration of heterogeneous application systems within an enterprise and between enterprises. Web services are widely considered as enabling technologies for implementing application services under SOA. Web services composition is a flexible means to build various application services. In web services composition, one primary task is to discover and select proper services according to user requests and preferences. In this paper, we present SLF4SS, a self-learning framework for services selection.