Process diagnostics using trace alignment: Opportunities, issues, and challenges
Process diagnostics using trace alignment: Opportunities, issues, and challenges
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DOI：
10.1016/j.is.2011.08.003
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发表时间：
2012-04-01
影响因子：
3.7
通讯作者：
van der Aalst, Wil M. P.
中科院分区：
文献类型：
--
作者：
Bose, R. P. Jagadeesh Chandra;van der Aalst, Wil M. P.
业务流程在各种数据源(例如，审计跟踪、数据库和事务日志)中留下跟踪。因此，每个流程实例都可以通过跟踪(即事件序列)来描述。流程挖掘技术能够从这些踪迹中提取知识，并为业务流程分析技术提供了一个受欢迎的扩展。最近，流程挖掘技术已被各种商业BPM系统(例如，BPM垂直条一号、Futura Reflect、Aris PPM、Fujitsu InterStage、Businessscape、Iontas PDF和QPR PA)所采用。不幸的是，传统的进程发现算法在处理结构化程度较低的进程时存在问题。由此产生的模型难以理解，甚至具有误导性。因此，我们提出了一种新的基于轨迹对齐的方法。目标是以一种可以轻松查看事件日志的方式对齐跟踪。痕迹对齐可用于在分析的早期阶段探索过程，并在分析的后期阶段回答特定问题。因此，它补充了现有的专注于发现和一致性检查的过程挖掘技术。所提出的技术已经作为插件在PROM框架中实现。我们报告了一个合成事件日志和两个真实事件日志上的跟踪对齐结果，并表明跟踪对齐在过程诊断工作中具有重要的前景。(C)2011爱思唯尔有限公司。保留所有权利。
Business processes leave trails in a variety of data sources (e.g., audit trails, databases, and transaction logs). Hence, every process instance can be described by a trace, i.e., a sequence of events. Process mining techniques are able to extract knowledge from such traces and provide a welcome extension to the repertoire of business process analysis techniques. Recently, process mining techniques have been adopted in various commercial BPM systems (e.g., BPM vertical bar one, Futura Reflect, ARIS PPM, Fujitsu Interstage, Businesscape, Iontas PDF, and QPR PA). Unfortunately, traditional process discovery algorithms have problems dealing with less structured processes. The resulting models are difficult to comprehend or even misleading. Therefore, we propose a new approach based on trace alignment. The goal is to align traces in such a way that event logs can be explored easily. Trace alignment can be used to explore the process in the early stages of analysis and to answer specific questions in later stages of analysis. Hence, it complements existing process mining techniques focusing on discovery and conformance checking. The proposed techniques have been implemented as plugins in the ProM framework. We report the results of trace alignment on one synthetic and two real-life event logs, and show that trace alignment has significant promise in process diagnostic efforts. (C) 2011 Elsevier Ltd. All rights reserved.