Advanced Information Systems Engineering

38th International Conference, CAiSE 2026, Verona, Italy, June 8–12, 2026, Proceedings, Part II
Erscheinungsjahr 2026
ISBN: 978-3-032-28116-6
Verlag: Springer

Buch, Englisch, 452 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Computer Science

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.

Zielgruppe

Research

Autoren/Hrsg.

Fuentes, Lidia

Plebani, Pierluigi

Combi, Carlo

Reijers, Hajo

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
• Mathematik | Informatik EDV | Informatik Betriebssysteme
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Geistes- und Sozialwissenschaften

Inhaltsverzeichnis

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.