[1]蒋艳荣,李卫华,杨劲涛.一种基于知识树和约束的柔性活动动态细化方法[J].智能系统学报,2017,12(2):158-165.[doi:10.11992/tis.201603009]
JIANG Yanrong,LI Weihua,YANG Jintao.A dynamic refinement approach for flexible activity based on knowledge tree and constraints[J].CAAI Transactions on Intelligent Systems,2017,12(2):158-165.[doi:10.11992/tis.201603009]
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《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
12
期数:
2017年第2期
页码:
158-165
栏目:
学术论文—知识工程
出版日期:
2017-05-05
- Title:
-
A dynamic refinement approach for flexible activity based on knowledge tree and constraints
- 作者:
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蒋艳荣, 李卫华, 杨劲涛
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广东工业大学 计算机学院, 广东 广州 510006
- Author(s):
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JIANG Yanrong, LI Weihua, YANG Jintao
-
School of Computer, Guangdong University of Technology, Guangzhou 510006, China
-
- 关键词:
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柔性工作流; 动态细化; 时序约束; 工作流生成; 过程建模
- Keywords:
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flexible workflow; dynamic refinement; temporal constraints; workflow generation; process modeling
- 分类号:
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TP391
- DOI:
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10.11992/tis.201603009
- 摘要:
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柔性工作流在应对业务建模过程中的动态不确定因素、提高工作流系统的柔性具有巨大的优势,然而,柔性活动的动态细化一直是柔性工作流建模和应用的一个难点。因此,提出一种基于知识树和约束的柔性活动动态细化方法。该方法以知识树的包含和泛化关系作为启发信息,以活动选取约束和时序约束作为指导和校验,实现柔性活动的动态细化。在介绍了知识树及其蕴含关系以及活动选取约束和时序约束规则的基础上,给出了柔性活动的动态细化算法,描述了活动选取校验和时序约束校验算法。最后给出了算法的实现和实例分析,其结果表明了所提方法的有效性,能够很好地解决柔性活动的细化问题。
- Abstract:
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Flexible workflow systems offer huge advantages in addressing dynamic uncertain factors during the modeling period; however, the dynamic refinement of flexible activities remains a challenge in the modeling and application of flexible workflows. Therefore, we propose a dynamic refinement approach of flexible activities based on a knowledge tree and various constraints. More specifically, we used the inclusion and generalization relationships of knowledge trees as heuristic information; further, we used activity selection constraints and temporal constraints to guide our verification processes. Given the introduction of a knowledge tree and its containing relationships, as well as activity selection constraint and temporal constraint rules, we provide a dynamic refinement algorithm and an algorithm for activity selection checkout and temporal constraint checkup. Finally, we provide a realization of our algorithms and offer case analyses. Our results show that our proposed algorithms are effective and can solve the problem of dynamic refinement of flexible activities quite well.
备注/Memo
收稿日期:2016-3-6;改回日期:。
基金项目:国家自然科学基金项目(61142012);广东省科技计划项目(2015B010128005,2013B021800115).
作者简介:蒋艳荣,男,1976年生,讲师,博士,主要研究方向为机器智能、上下文感知计算、智能交互;发表学术论文20余篇,其中被SCI检索8篇、EI/ISTP检索10余篇;李卫华,女,1957年生,教授,博士,主要研究方向为智能软件、网络信息系统、面向Agent计算。发表学术论文40余篇,出版著作多部;杨劲涛,男,1971年生,博士,主要研究方向为Web服务计算、模式识别、医学图像处理技术,发表学术论文20余篇。
通讯作者:蒋艳荣. E-mail:yrjiang@gdut.edu.cn.
更新日期/Last Update:
1900-01-01