science departm ent,Fujian norm aluniversity, 2.State key laboratory ofsoftw are engineering,W uhan U niversity *pinggong@ fjnu.edu.cn A bstract B usiness processes com pliance m onitoring checks w hether running business processes com ply w ith involved sem antic constraints,i.e.,com pliance rules.B usiness processes in m odern enterprise are rarely supported by a single and centralized w orkflow system ,but instead im plem ented over different applications (e.g.,CR M ,ER P,W fM S,and legacy system s).The running data (i.e.,event) aboutprocess executions are scattered across these applications.U nder the circum stances,understanding the com pliance ofrunning processes entails the com pliance m onitoring enabling to correlate events from different applications and even different cases (event correlation herein is identifying events related to the sam e com pliance rule instance).This paper introduces a fram ew ork nam ed as bpCM on for business process com pliance m onitoring.bpCM on consists of an expressive com pliance rule language ECL and a rule system ERS. ECL is a pattern-based form allanguage for specifying com pliance rules ofm ultiple process perspectives,and also allow s for describing event-correlation condition.ER S,generated from com pliance rules in ECL,in turn plays as a com pliance m onitor enabling to correlate events efficiently by m eans of an indexing structure created from eventcorrelation conditions.The applicability ofbpCM on is dem onstrated by experim ents on a real-w orld data set.O verall, bpCM on enables business process com pliance m onitoring m eeting real-w orld requirem ents. K eyw ords: B usiness process com pliance,com pliance m onitoring,eventcorrelation
This paper describes the concept of workflow merge and methods for merging business processes. We append effect annotations to activities of business process, use RPSTs divided the process graph to fragments then accumulate these effects according to these SESE fragments, detect exact clone and approximate clone between the two process models, finally design a merging algorithm to consolidate two processes. It is shown that to avoid invalid merges, one choose merge unit is SESE fragments, we also raise issues of more complex merge problems, such as semantic annotations.
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