Summary of Intelligent Cross-organizational Process Mining: a Survey and New Perspectives, by Yiyuan Yang et al.
Intelligent Cross-Organizational Process Mining: A Survey and New Perspectives
by Yiyuan Yang, Zheshun Wu, Yong Chu, Zhenghua Chen, Zenglin Xu, Qingsong Wen
First submitted to arxiv on: 15 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computational Engineering, Finance, and Science (cs.CE); Databases (cs.DB); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The survey paper delves into the growing significance and ongoing trends in process mining, a high-level field in data mining that enhances operational efficiency and decision-making. The authors propose a holistic framework for intelligent process analysis, leveraging artificial intelligence to offer sophisticated solutions for complex data analysis. This framework integrates advanced machine learning techniques to enhance predictive capabilities, streamline processes, and facilitate real-time decision-making. The paper outlines methodologies in cross-organizational settings, highlighting challenges and opportunities. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Process mining helps organizations make better decisions and run more efficiently. This paper looks at how process mining uses artificial intelligence to analyze complex data from multiple sources. It proposes a new way to analyze processes that involves machine learning techniques. This can help predict what might happen in the future, streamline processes, and make quick decisions. |
Keywords
» Artificial intelligence » Machine learning
