关键词: 业务流程, 流程行为, 流程相似性, 流程推荐, 人工智能, 神经网络

Abstract: Business process modeling recommendation is one of the main ways to assist process modeling. Process similarity is the core technology of this method, which directly affects the accuracy of process recommendation. Process similarity includes two aspects：Graph structure similarity and behavior similarity. In order to solve the problem of difficulty in quantifying process similarity and low accuracy, a single-layer neural network-based process similarity quantification method is proposed. Firstly, this paper builds a behavior-based process system, establishes business processes, independent paths, and function expression relationships between process nodes. Secondly, it uses one-hot coding to represent the process nodes with initialization vectors, and establishes a single-layer neural network model to record the process trajectory of log data as the training set, the process nodes are mapped to a low-dimensional continuous vector space, the vector of each process node is obtained., and the vector form of the business process is obtained. Finally the similarity between the processes is calculated by the cosine similarity. The accuracy of the proposed method is verified through experiments, and the application of the method in the field of process recommendation is introduced.

Key words: business process, process behavior, process similarity, process recommendation, artificial intelligence, neural network