Title :
SLF4SS: Facilitating Flexible Services Selection
Author :
Wang, Hongbing ; Wang, Yifei ; Huang, Joshua Zhexue ; Xu, Xun
Author_Institution :
Dept. of Comput. Sci. & Eng., Southeast Univ., Nanjing
Abstract :
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
Keywords :
Web services; fuzzy logic; software selection; unsupervised learning; SLF4SS; SOA; Web services; fuzzy logic; machine learning; self-learning framework; services selection; Availability; Computer science; Constraint optimization; Costs; Delay; Fuzzy logic; Intelligent agent; Learning systems; Service oriented architecture; Web services;
Conference_Titel :
Web Intelligence and Intelligent Agent Technology Workshops, 2006. WI-IAT 2006 Workshops. 2006 IEEE/WIC/ACM International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2749-3
DOI :
10.1109/WI-IATW.2006.122
