mlsanityData to 7 Oct 2026

Intelligent Cross-Organizational Process Mining: A Survey and New Perspectives

arXiv 2407.11280 ↗First posted 15 Jul 2024cs.AI cs.CE cs.DBcited by 2

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Abstract (arXiv)

Process mining, as a high-level field in data mining, plays a crucial role in enhancing operational efficiency and decision-making across organizations. In this survey paper, we delve into the growing significance and ongoing trends in the field of process mining, advocating a specific viewpoint on its contents, application, and development in modern businesses and process management, particularly in cross-organizational settings. We first summarize the framework of process mining, common industrial applications, and the latest advances combined with artificial intelligence, such as workflow optimization, compliance checking, and performance analysis. Then, we propose a holistic framework for intelligent process analysis and outline initial methodologies in cross-organizational settings, highlighting both challenges and opportunities. This particular perspective aims to revolutionize process mining by leveraging artificial intelligence to offer sophisticated solutions for complex, multi-organizational data analysis. By integrating advanced machine learning techniques, we can enhance predictive capabilities, streamline processes, and facilitate real-time decision-making. Furthermore, we pinpoint avenues for future investigations within the research community, encouraging the exploration of innovative algorithms, data integration strategies, and privacy-preserving methods to fully harness the potential of process mining in diverse, interconnected business environments.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 21 of its 88 references that are in the map. First posted on arXiv 15 Jul 2024.

Builds on

21 of 88 references.

References · 21

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9 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Towards Deep Encrypted Training: Low-Latency, Memory-Efficient, and High-Throughput Inference for Privacy-Preserving Neural Networkscited by 0
  2. 2026From Event Logs to Governed Action: A BlueSky Agenda for Agentic Process Miningcited by 0