哈尔滨商业大学学报（自然科学版）2026，Vol.42Issue(3)：313-321,9.
融合行为轮廓与Transformer的下一活动预测框架
Next activity prediction framework incorporating behavioral profiles and Transformer
摘要
Abstract
Predicting the occurrence of the next activity in a process has become a key task in process intelligence.Existing research mainly focused on the temporal modeling of event sequences,with less attention paid to the modeling and utilization of structural behavioral relationships between activities.Therefore,a next activity prediction method was proposed.The method integrated the behavioral profile matrix and the Transformer structure,aiming to simultaneously mine the structural information and contextual semantic information in the process.The method extracted the behavioral profile matrix from the event log to describe the sequential and logical relationships between activities;used a convolutional neural network(CNN)to extract spatial pattern features from the matrix and employed a Transformer model to model the prefix event sequence;predicted the next activity through feature fusion and a multi-layer perceptron.Experiments on multiple real business process log datasets showed that the proposed method achieved superior prediction performance,verifying the effectiveness of the fusion modeling of structural information and temporal semantics.This paper provided a new modeling approach for improving prediction accuracy in complex process scenarios.关键词
下一活动预测/行为轮廓矩阵/卷积神经网络/Transformer/流程挖掘/预测性过程监控Key words
next activity prediction/behavioral profile matrix/convolutional neural network/Transformer/process mining/predictive process monitoring分类
信息技术与安全科学引用本文复制引用
董昊然,方娜..融合行为轮廓与Transformer的下一活动预测框架[J].哈尔滨商业大学学报（自然科学版）,2026,42(3):313-321,9.基金项目
国家自然科学基金资助项目(61572035,61402011) （61572035,61402011）
安徽省重点研究与开发计划项目(2022a05020005) （2022a05020005）
安徽省自然科学基金项目(水科学联合基金,2308085US11) （水科学联合基金,2308085US11）
