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Hierarchical conformance checking of process models based on event logs

機譯:基于事件日志的流程模型的分層一致性檢查

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摘要

Process mining techniques aim to extract knowledge from event logs. Conformance checking is one of the hard problems in process mining: it aims to diagnose and quantify the mismatch between observed and modeled behavior. Precise conformance checking implies solving complex optimization problems and is therefore computationally challenging for real-life event logs. In this paper a technique to apply hierarchical conformance checking is presented, based on a state-of-the-art algorithm for deriving the subprocesses structure underlying a process model. Hierarchical conformance checking allows us to decompose problems that would otherwise be intractable. Moreover, users can navigate through conformance results and zoom into parts of the model that have a poor conformance. The technique has been implemented as a ProM plugin and an experimental evaluation showing the significance of the approach is provided.
機譯:流程挖掘技術(shù)旨在從事件日志中提取知識。一致性檢查是流程挖掘中的難題之一:它旨在診斷和量化觀察到的行為與建模行為之間的不匹配。精確的一致性檢查意味著要解決復(fù)雜的優(yōu)化問題,因此對于實際事件日志而言,在計算上存在挑戰(zhàn)。在本文中,基于最新算法,提出了一種用于應(yīng)用層次一致性檢查的技術(shù),該算法用于推導(dǎo)流程模型下的子流程結(jié)構(gòu)。分層一致性檢查使我們能夠分解原本難以處理的問題。此外,用戶可以瀏覽一致性結(jié)果并放大模型中一致性較差的部分。該技術(shù)已實現(xiàn)為ProM插件,并提供了表明該方法重要性的實驗評估。

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