基于贝叶斯网络的业务上下文认知模型构建方法
doi: 10.3724/SP.J.1146.2006.00980
Construction Approach for Bayesian Network-Based Service Context Recognition Model
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摘要: 业务上下文信息的处理是未来泛在融合电信业务智能化的基础，而不确定性是业务上下文信息不可回避的一个问题。该文利用贝叶斯网络理论，提出一种支持不确定性推理的业务上下文认知模型的构建方法，用来解决具有不确定性的业务上下文信息的融合和聚类，并通过仿真实验验证了模型的合理性和可用性。Abstract: The process of service context information is the foundation of future ubiquitous convergent telecommunication services intelligence. Uncertainty is an unavoidable problem of service context information process. In this article, based on Bayesian network theory, one construction approach for service context recognition model of supporting uncertainty reasoning is presented to resolve the convergence and classification of uncertain service context information. Furthermore, the rationality and usability of this model are verified by simulations.
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