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工作流生成中的一种流程模式知识优化方法

Approach for process pattern optimization in workflow generation
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摘要 基于模式的工作流生成利用规划技术和业务知识实现了工作流自动创建。流程模式知识的优劣直接影响到工作流生成结果的正确性。提出了一个针对流程模式的知识优化方法。在人工建模的基础上,针对流程模式知识构建场景分类器。利用流程规划运行的历史数据,通过机器学习对流程模式进行调整与优化,保证了工作流创建的正确性。 Pattern-oriented workflow generation has utilized AI planning technologies and knowledge for automatic workflow construction.The quality of process pattern has essential impact on workflow generation resuh.This paper proposes an approach for pattern knowledge optimization.Based on expert modeling resuh,scenario classifier is constructed.Process pattern can be improved by classifier training resuh on planning history,which enable workflow generation more reliable.
作者 张少华 向勇 沈浴竹 史美林
机构地区 清华大学计算机科学与技术系
出处 《计算机工程与应用》 CSCD 北大核心 2008年第21期12-16,共5页 Computer Engineering and Applications
基金 国家自然科学基金( the National Natural Science Foundation of China under Grant No.90412009)
关键词 工作流生成 流程模式 场景分类器训练 workflow generation process pattern scenario classifier training
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献10

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二级参考文献11

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共引文献7

计算机工程与应用
2008年 第21期

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