Discovery of temporal patterns from process instances
Existing work in process mining focuses on the discovery of the underlying process model from their instances.In this paper,we do not assume the existence of a single process model to which all process instances comply,and the goal is to discover a set of frequently occurring temporal patterns.Discovery of temporal patterns can be applied to various application domains to support crucial business decision-making.In this study,we formally defined the temporal pattern discovery problem,and developed and evaluated three different temporal pattern discovery algorithms,namely TP-Graph,TP-Itemset and TP-Sequence.Their relative performances are reported.
Process mining Knowledge discovery Data mining Temporal patterns Association rules Sequential patterns
San-Yih Hwang Chih-Ping Wei Wan-Shiou Yang
Department of Information Management,National Sun Yat-Sen University,Kaohsiung,Taiwan,ROC
国内会议
南京
英文
1-20
2013-11-01（万方平台首次上网日期，不代表论文的发表时间）