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.

过程挖掘在提升组织运营效率和决策制定方面发挥着关键作用。本研究针对过程挖掘领域的重要性和不断发展的趋势，着重介绍了其内容、应用和在现代企业和过程管理中的发展，特别是在跨组织环境中。通过整合人工智能和先进的机器学习技术，我们可以提供复杂、多组织数据分析的先进解决方案，从而提高预测能力、优化流程和促进实时决策。未来的研究方向包括创新算法、数据整合策略和隐私保护方法，以充分利用过程挖掘在各种互相关联的商业环境中的潜力。

智能跨组织流程挖掘：调查和新视角