电子学报 ›› 2019, Vol. 47 ›› Issue (12): 2596-2601.DOI: 10.3969/j.issn.0372-2112.2019.12.020

• 学术论文 • 上一篇    下一篇

基于加权流关系的流程相似性算法

段瑞, 方欢, 詹悦   

  1. 安徽理工大学数学与大数据学院, 安徽淮南 232001
  • 收稿日期:2018-12-09 修回日期:2019-02-25 出版日期:2019-12-25
    • 通讯作者:
    • 方欢
    • 作者简介:
    • 段瑞 男,1993年3月出生于安徽省涡阳县.现为安徽理工大学数学与大数据学院硕士研究生.主要研究方向为业务流程过程挖掘,Petri网理论与应用.E-mail:85768312@qq.com;詹悦 女,1994年3月出生于安徽省安庆市太湖县.现为安徽理工大学数学与大数据学院硕士研究生.主要研究方向为Petri网理论与应用.E-mail:2272350170@qq.com
    • 基金资助:
    • 国家自然科学基金 (No.61472003,No.61402011,No.61572035); 安徽省自然科学基金 (No.1608085QF149); 安徽省高校优秀青年人才基金 (No.gxyqZD2018038); 安徽省博士后基金 (No.2018B288)

Process Similarity Algorithm Based on Weighted Flow Relationship

DUAN Rui, FANG Huan, ZHAN Yue   

  1. Dept of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, Anhui 232001, China
  • Received:2018-12-09 Revised:2019-02-25 Online:2019-12-25 Published:2019-12-25
    • Corresponding author:
    • FANG Huan
    • Supported by:
    • National Natural Science Foundation of China (No.61472003, No.61402011, No.61572035); Natural Science Foundation of Anhui Province (No.1608085QF149); Fund for Distinguished Young Talents in Higher Education of Anhui Province (No.gxyqZD2018038); Postdoctoral Foundation of Anhui Province (No.2018B288)

摘要: 为了提高从企业模型库中检索模型的效率,提出一种基于加权流关系的相似性算法,记作WF.首先,本文设计加权流关系集的生成算法,生成算法通过广度优先搜索方法遍历除输出库所外的所有节点及流关系,为每个流关系唯一分配权重,生成加权流关系集;其次,WF算法基于加权流关系集计算出加权变迁集,并依据WF相似性定义计算相似性;最后,通过实验及算法的时间复杂度分析比较表明:算法是正确且唯一确定结果的,且WF算法具有良好的性能.

 

关键词: Petri网, 加权流关系, 加权变迁, 流程相似性

Abstract: In order to improve the efficiency of retrieving models from enterprise model library, a similarity algorithm based on weighted flow relationship is proposed, regarded as WF. Firstly, this paper designs a weighted flow relationship set generation algorithm. The generation algorithm traverses all nodes and flow relationships except the output place by breadth-first search method. The weight is assigned to each flow relationship to generate a weighted flow relationship set. Secondly, the WF algorithm calculates the weighted transition set based on the weighted flow relationship set, and calculates the similarity according to the WF similarity definition. Finally, through experimental and analyzing the time complexity of the algorithm results show that the proposed algorithm is correct and unique to determine the result and the algorithm has good performance.

 

Key words: Petri nets, weighted flow relationship, weighted transition, process similarity

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