  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.
