Lakshmanan et al. 2013 — Instance-Specific Markov PPM for Semi-Structured Processes

Early classical-probabilistic PPM. Targets case-oriented, semi-structured processes (insurance claims, healthcare, prescription orders) where activity order is determined by case-worker judgement, not a fixed workflow.

Contribution

Introduces an instance-specific PPM: transition probabilities are customised per case based on its document content.
Shows how instance-specific PPMs can be lifted to a Markov chain (with an extended-space construction to handle parallel tasks).
Demonstrates on a simulated automobile-insurance-claims process.

Significance in the PPM landscape

Pre-deep-learning; representative of the classical probabilistic-model lineage that Evermann 2017 and Tax 2017 later contrasted their neural approaches against. Closely related to CMMN-style case management (frameworks/cmmn).

Connections

Concepts: concepts/predictive-process-monitoring · concepts/outcome-prediction · concepts/next-activity-prediction Frameworks: frameworks/cmmn Authors: entities/geetika-lakshmanan · entities/merve-unuvar