关键词: 表示学习, 过程模型匹配, 活动向量, 业务过程管理

Abstract: In recent years,process aware information system has been widely applied in various enterprises and institutions,generating a large number of business process models.The management of massive business process models has become an important task in business process management,in which Process Model Matching (PMM) is one of the key technologies.Most of the PMM approaches only rely on activity tag information and do not yet achieved the desired accuracy.A novel PMM approach based on representation learning was proposed.The activities in a business process model were represented as multi-dimensional real-valued vectors that encoded the context information and relationship information contained in the business process model.A vector space mapping model was proposed to model the activity vectors from different business process models,thus enabling activity matching between process models.Experimental results on public datasets verified that the proposed approach outperformed traditional PMM approaches based on syntax,semantic and structure information.

Key words: representation learning, process model matching, activity vector, business process management