摘要：Process mining is getting much attentions and interests in the development of the web-based information technique (IT) field. Process conformance, one of process mining techniques, may be the most common method used to find out the (dis)similar working process(es). The distinguishing processes found are greatly instrumental in making business decisions, such as conduction strategies, service tactics, manufacturing process, …, etc., and further to advance their working efficiency. Several process conformance approaches have been developed and discussed over the past decade, but those discussions involving in the investigation to seek for reasons why the working processes are (un)conformable are rare. To advance the function of the process conformance, this paper introduces the two parameters, Support and Confidence, used for newly defining the tinguishability among various processes; meanwhile, they are also taken to identify the roots resulting to the process distinguishing. “Support” parameter functions as the evaluation of the process similarity based on the working activity sequences ( or called “from-to” workflows) and on the relationships among the various processes evaluated; “Confidence” as the measure of the process relationships defined by a ratio of the identical activities within two processes to the total activities of each individual process. Moreover, the two proposed parameters had also been applied to a real case, in which the nursing processes worked in the pediatrics department of a hospital were measured and improved. To the best knowledge of the authors, there does not have an exact technique that, so far, is intact of considering the whole situation where all of the process conformance factors are involved; even the presentation of this paper cannot be avoidable. Nevertheless, this paper truly provides a way to find a certain degree of a lower bound of the process distinguishability through the two proposed conformance parameters.
关键词：process conformance; process mining; Petri nets; distinguishability; process similarity
