关键词: 序列模式, Markov模型, 基于案例的推理, 业务流程管理, 推荐系统

Abstract: The business process management and knowledge management were independent of each other,which made a challenge to provide effective knowledge support for process participants.To solve this problem,a process-oriented knowledge recommendation system by mining knowledge patterns from historical process executions was proposed.Process context was modeled with role information of participants and description text of process problems.A case repository was built by integrating process execution logs and knowledge reference logs.On this basis,a case based reasoning approach was utilized to reason the knowledge intention for new process contexts.Further,the topic-wise Markov model and sequential mining were used to analyze participants'learning patterns on each knowledge topic,and more helpful knowledge sequences were recommended in accordance with learners'cognitive patterns.The effectiveness of the proposed method was evaluated with a real-life software development process,and results indicated that the system could achieve better precision and recall.

Key words: sequential pattern, Markov model, case based reasoning, business process management, recommender system