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Advanced Information Systems Engineering

38th International Conference, CAiSE 2026, Verona, Italy, June 8–12, 2026, Proceedings, Part...

Lidia Fuentes Pierluigi Plebani Carlo Combi Hajo Reijers

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English
Springer Nature Switzerland AG
09 June 2026
The two-volume set LNCS 16558 + 16559 constitutes the proceedings of the 38th International Conference on Advanced Information Systems Engineering, CAiSE 2026, which took place in Verona, Italy, during June 2026.

The 46 full papers included in the proceedings were carefully reviewed and selected from 331 submissions. The papers were organized in topical sections as follows: 

Part I: Enterprise Intelligence, Complexity, and Decision Support; Forecasting, Drift, and Prescriptive Process Analytics; Conceptual Modeling, Ontologies, and Value; Enriching Process Mining with Context and Sustainability; Human-in-the-Loop Engineering and Development Practices; Process Discovery and Analysis; Engineering AI Systems across Cloud, Edge, and Cyber-Physical Environments; 

Part II: LLM-Driven Modeling and Human–AI Collaboration; Agent-Based and Multi-Stakeholder Process Interaction; LLMs and AI for Process Understanding; Predictive and Neuro-Symbolic Process Analytics; Responsible, Fair, and Human-Centered AI; Object-Centric Process Mining and Conformance; Process Mining Data Quality and Repair.

 
Edited by:   , , ,
Imprint:   Springer Nature Switzerland AG
Country of Publication:   Switzerland
Dimensions:   Height: 235mm,  Width: 155mm, 
ISBN:   9783032281166
ISBN 10:   3032281164
Series:   Lecture Notes in Computer Science
Pages:   452
Publication Date:  
Audience:   Professional and scholarly ,  College/higher education ,  Undergraduate ,  Further / Higher Education
Format:   Paperback
Publisher's Status:   Active
LLM-Driven Modeling and Human–AI Collaboration.- Agent-Based and Multi-Stakeholder Process Interaction.- LLMs and AI for Process Understanding.- Predictive and Neuro-Symbolic Process Analytics.- Responsible, Fair, and Human-Centered AI.- Object-Centric Process Mining and Conformance.- Process Mining Data Quality and Repair.

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