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ProVEx: A Contrastive Explanation Framework for Process Variant Analysis

https://doi.org/10.2139/ssrn.6963087
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-00847-5_32openalex-snapshot
Multi-perspective Comparison of Business Process Variants Based on Event Logs
inferredcites →https://doi.org/10.1007/978-3-319-98648-7_9openalex-snapshot
Unbiased, Fine-Grained Description of Processes Performance from Event Data
inferredcites →https://doi.org/10.1007/978-3-662-49851-4openalex-snapshot
Process Mining: Data Science in Action
inferredcites →https://doi.org/10.1007/s10618-016-0488-4openalex-snapshot
Explaining clusterings of process instances
inferredcites →https://doi.org/10.1016/j.artint.2018.07.007openalex-snapshot
Explanation in artificial intelligence: Insights from the social sciences
inferredcites →https://doi.org/10.1016/j.engappai.2023.107028openalex-snapshot
Trace encoding in process mining: A survey and benchmarking
inferredcites →https://doi.org/10.1016/j.inffus.2019.12.012openalex-snapshot
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
inferredcites →https://doi.org/10.1016/j.inffus.2021.05.009openalex-snapshot
Notions of explainability and evaluation approaches for explainable artificial intelligence
inferredcites →https://doi.org/10.1016/j.inffus.2024.102301openalex-snapshot
Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions
inferredcites →https://doi.org/10.1086/289648openalex-snapshot
Contrastive Explanation and Causal Triangulation
inferredcites →https://doi.org/10.1109/access.2024.3361650openalex-snapshot
Tuning Machine Learning to Address Process Mining Requirements
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