方法证据记录
Process Mining
Process Mining is a data-driven discipline that extracts knowledge about real-world processes from event logs recorded by information systems. Introduced systematically by Wil van der Aalst, with foundational workflow mining formalized in 2004 and consolidated in the 2016 textbook, the technique bridges data science and process management. It enables organizations to discover how processes actually execute, check whether execution conforms to prescribed models, and diagnose performance bottlenecks — all directly from digital traces.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Process Mining
分类方法记录 · process-pipeline / process-mining
- van der Aalst, W. M. P. (2016). Process Mining: Data Science in Action (2nd ed.). Springer. · ISBN 978-3-662-49850-7
- van der Aalst, W., Weijters, T., & Maruster, L. (2004). Workflow mining: Discovering process models from event logs. IEEE Transactions on Knowledge and Data Engineering, 16(9), 1128–1142. · DOI 10.1109/TKDE.2004.47
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