Towards Knowledge-Centric Process Mining
Process analytic approaches play a critical role in supporting the practice of business process management and continuous process improvement by leveraging process-related data to identify performance bottlenecks, extracting insights about reducing costs and optimizing the utilization of available resources. Process analytic techniques often have to contend with real-world settings where available logs are noisy or incomplete. In this paper we present an approach that permits process analytics techniques to deliver value in the face of noisy/incomplete event logs. Our approach leverages knowledge graphs to mitigate the effects of noise in event logs while supporting process analysts in understanding variability associated with event logs.
Code (0)
등록된 구현이 없습니다.
Tasks
Knowledge GraphsManagementSimilar Papers 제목 키워드 기반
Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective
Given the complexity and lack of transparency in deep neural networks (DNNs), extensive efforts have been made to make these systems more interpretable or explain their behaviors in accessible terms. Unlike most reviews,…
Data ValuationDecision MakingExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)+1Process Comparison Using Object-Centric Process Cubes
Process mining provides ways to analyze business processes. Common process mining techniques consider the process as a whole. However, in real-life business processes, different behaviors exist that make the overall proc…
ObjectAnalyzing An After-Sales Service Process Using Object-Centric Process Mining: A Case Study
Process mining, a technique turning event data into business process insights, has traditionally operated on the assumption that each event corresponds to a singular case or object. However, many real-world processes are…
ObjectDefining Cases and Variants for Object-Centric Event Data
The execution of processes leaves traces of event data in information systems. These event data can be analyzed through process mining techniques. For traditional process mining techniques, one has to associate each even…
AttributeERPObjectA Framework for Extracting and Encoding Features from Object-Centric Event Data
Traditional process mining techniques take event data as input where each event is associated with exactly one object. An object represents the instantiation of a process. Object-centric event data contain events associa…
Object