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Estimating Global Completeness of Event Logs: A Comparative Study
IEEE Transactions on Services Computing ( IF 8.1 ) Pub Date : 2018-01-01 , DOI: 10.1109/tsc.2018.2805912
Jisheng Pei , Lijie Wen , Hedong Yang , Jianmin Wang , Xiaojun Ye

Event logs are the basis of process mining techniques and tools that extract process behavior information for better understanding and optimization of business processes. While it has been widely realized that the degree of completeness of event logs may largely determine the effectiveness of these techniques, how to estimate the completeness of event logs has not yet been fully addressed. This is mainly because ground-truth process models are usually unknown. To attack this problem, we pay a closer look to several concepts and implicit assumptions in the log completeness estimation problem and characterize it as a special case of the species estimation problem in the field of statistics. Although species estimation is still an open problem, a number of statistic models and techniques with approximate solutions have been available. To investigate the relevance of these methods for event log completeness estimation, we have designed and conducted a wide scope of empirical study and quantitative experiments on both real-world and synthesized event logs to compare the performance of these methods. In addition, the completeness estimation of several important and widely used real-world events logs are reported for the first time together with some best practice experience learned through this research.

中文翻译:

估计事件日志的全局完整性:一项比较研究

事件日志是流程挖掘技术和工具的基础,可以提取流程行为信息以更好地理解和优化业务流程。虽然人们普遍认识到事件日志的完整性程度可能在很大程度上决定这些技术的有效性,但如何估计事件日志的完整性尚未完全解决。这主要是因为地面实况过程模型通常是未知的。为了解决这个问题,我们仔细研究了日志完整性估计问题中的几个概念和隐含假设,并将其描述为统计领域中物种估计问题的一个特例。尽管物种估计仍然是一个悬而未决的问题,但已经有许多具有近似解的统计模型和技术可用。为了研究这些方法与事件日志完整性估计的相关性,我们对真实世界和合成事件日志设计并进行了广泛的实证研究和定量实验,以比较这些方法的性能。此外,首次报告了几个重要且广泛使用的现实世界事件日志的完整性评估以及通过本研究学到的一些最佳实践经验。
更新日期:2018-01-01
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