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SLF4SS: Facilitating Flexible Services Selection

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4 Author(s)
Hongbing Wang ; Dept. of Comput. Sci. & Eng., Southeast Univ., Nanjing ; Yifei Wang ; Huang, J.Z. ; Xun Xu

In this paper, we present SLF4SS, a self-learning framework for services selection. The main features of SLF4SS include (1) learning from previous match samples to help users discover more appropriate services, (2) using multi-dimensional properties to represent services for evaluation and selection, (3) optimizing the overall property of composite service appropriate to customer's constraints and preferences, and (4) addressing users uncertain, vague requests. SLF4SS can simplify selection of suitable Web services in building high level services for various business applications, reduce implementation cost, and shorten the time of deploying enterprises applications based on SOA

Published in:

Web Intelligence and Intelligent Agent Technology Workshops, 2006. WI-IAT 2006 Workshops. 2006 IEEE/WIC/ACM International Conference on

Date of Conference:

Dec. 2006

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