摘要
为在流程相似度计算中加入流程间深层语义关联的度量,同时在流程节点较多的情况下,实现流程匹配算法在寻优时间复杂度和相似度匹配输出值两方面的综合优化,提出一种面向流程的遗传匹配算法,将遗传算法引入并应用在流程语义和结构的相似度计算寻优过程中.确定遗传算法的参数编码方式,并利用贪婪算法进行初始种群的设置,定义各个遗传算子,提出有效的简化策略,解决了流程节点较多时流程匹配过程寻优问题.实验研究表明,在流程节点数较多时,本文算法在寻优时间花费和相似度值两方面的折中优化性能明显优于其他两种算法.将遗传算法应用到流程的相似度计算及其寻优过程,可以有效地控制时间复杂度并保证较好的匹配输出结果.
To calculate the process similarity with consideration of deep semantics correlation between business processes, and to optimize the time complexity and matching result when the node number of business process becomes larger and larger, a process matching method based on GA （ Genetic Algorithm） is put forward. This method is applied in similarity calculation for both process semantic and process structure, in which encoding is determined, and greedy algorithm is utilized to initialize the population of GA. By defining genetic operations and adopting some strategies for simplifying, the optimization of business process matching with large node number is fulfilled. As is expected, the experiments prove that the overall performance of algorithm proposed in this paper is better than the others that exist, especially when the count of process nodes grows to a large number. So it is concluded that the application of GA in business process similarity calculation and corresponding process optimization can effectively control the time complexity, meanwhile ensure the quality of the matching result, which shows a good practicability.
出处
《哈尔滨工业大学学报》
EI
CAS
CSCD
北大核心
2016年第7期150-155,共6页
Journal of Harbin Institute of Technology
基金
国家自然科学基金(51375395)
关键词
业务流程
文本相似度
语义知识库
匹配相似度
遗传算法
business process
text similarity
semantic repository
match similarity
genetic algorithm
作者简介
常关羽（1985-），男，博士研究生；通信作者：常关羽，dengxiao@mail．nwpu．edu．cn
杨海成（1959-），男，教授，博士生导师
