理解事件抽象解决问题的框架:事件抽象研究的现状

IF 2.7 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Data & Knowledge Engineering Pub Date : 2024-09-06 DOI:10.1016/j.datak.2024.102352
Jungeun Lim, Minseok Song
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引用次数: 0

摘要

事件抽象是将流程挖掘应用于现实世界场景的关键一步。然而,实践者在选择满足其特定需求的相关研究时往往面临挑战。为了解决这个问题,我们提出了一个理解事件抽象的综合框架,由四个关键部分组成:事件抽象子问题、流程属性考虑、事件抽象的数据类型以及事件抽象的各种方法。通过系统地研究这些组成部分,从业人员可以有效地识别符合其要求的研究。此外,我们还利用这一框架分析了现有研究,为从业人员提供了更清晰的当前研究视图,并建议扩大现有方法的应用范围。
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A framework for understanding event abstraction problem solving: Current states of event abstraction studies

Event abstraction is a crucial step in applying process mining in real-world scenarios. However, practitioners often face challenges in selecting relevant research for their specific needs. To address this, we present a comprehensive framework for understanding event abstraction, comprising four key components: event abstraction sub-problems, consideration of process properties, data types for event abstraction, and various approaches to event abstraction. By systematically examining these components, practitioners can efficiently identify research that aligns with their requirements. Additionally, we analyze existing studies using this framework to provide practitioners with a clearer view of current research and suggest expanded applications of existing methods.

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来源期刊
Data & Knowledge Engineering
Data & Knowledge Engineering 工程技术-计算机:人工智能
CiteScore
5.00
自引率
0.00%
发文量
66
审稿时长
6 months
期刊介绍: Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKE reaches a world-wide audience of researchers, designers, managers and users. The major aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of these systems.
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