作　　者： (孙晋永）; (古天龙）; (闻立杰）; (钱俊彦）; (孟瑜）;

机构地区： 西安电子科技大学计算机学院,西安710071 广西可信软件重点实验室（桂林电子科技大学）,广西桂林541004

出　　处： 《计算机研究与发展》 2017年第9期1880-1891,共12页

摘　　要： 相似语义工作流检索是语义工作流重用的首要任务.现有的相似语义工作流检索方法仅关注结构特征,忽略了行为特征,影响了检索到的相似语义工作流的整体质量,提高了语义工作流重用的代价.为此,提出一种结合行为和结构特征的2阶段相似语义工作流检索算法.使用任务紧邻关系集表达语义工作流的执行行为,结合领域知识构造语义工作流库的任务紧邻关系树索引和数据索引.针对查询语义工作流,先基于任务紧邻关系树索引和数据索引进行过滤得到候选语义工作流集;然后使用图匹配相似性算法对候选语义工作流集进行验证,得到排序的候选语义工作流集.实验结果表明,较主流的语义工作流检索算法,该方法的检索性能有较大提升,可以为工作流重用提供更高质量的语义工作流. Workflow reuse is an important method for modern enterprises and organizations to improve the efficiency of business process management （BPM）. Semantic workflows are domain knowledge- based workflows. The retrieval of similar semantic workflows is the first step for semantic workflow reuse. Existing retrieval algorithms of similar semantic workflows only focus on semantic workflows5 structural characteristics while ignoring their behavioral characteristics, which affects the overall quality of retrieved similar semantic workflows and increases the cost of semantic workflow reuse. To address this issue, a two-phase retrieval algorithm of similar semantic workflows is put forward based on behavioral and structural characteristics. A task adjacency relations （TARs） set is used to express a semantic workflow＇s behavior. A TARs trees index named TARTreelndex and a data index namedDatalndex are constructed combined with domain knowledge for the semantic workflows case base. For a given query semantic workflow, firstly, candidate semantic workflows are obtained by filteringthe semantic workflows case base with the TARTreelndex and Datalndex, then candidate semanticworkflows are verified and ranked with the graph matching similarity algorithm. Experiments showthat the proposed algorithm improves the retrieval performance of similar semantic workflowscompared with the existing popular retrieval algorithms for similar semantic workflows,so it canprovide high-quality semantic workflows for semantic workflow reuse.

关 键 词： 工作流重用 语义工作流 相似性检索 结构特征 行为特征 任务紧邻关系树索引