SLF4SS:促进灵活的服务选择

Hongbing Wang, Yifei Wang, J. Huang, Xun Xu
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引用次数: 0

摘要

在本文中,我们提出了一个用于服务选择的自学习框架SLF4SS。SLF4SS的主要特征包括:(1)从以前的匹配样本中学习,帮助用户发现更合适的服务;(2)使用多维属性来表示服务,以便进行评估和选择;(3)优化适合客户约束和偏好的组合服务的整体属性;(4)解决用户不确定、模糊的请求。SLF4SS可以简化在为各种业务应用程序构建高级服务时选择合适的Web服务,降低实现成本,并缩短基于SOA部署企业应用程序的时间
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SLF4SS: Facilitating Flexible Services Selection
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
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