Conceptual Modeling

43rd International Conference, ER 2024, Pittsburgh, PA, USA, October 28¿31, 2024, Proceedings
Herausgegeben:Maaß, Wolfgang; Han, Hyoil; Yasar, Hasan; Multari, Nick

• Broschiertes Buch

Produktbeschreibung

This book constitutes the proceedings of the 43rd International Conference on Conceptual Modeling, ER 2024, which took place in Pittsburgh, PA, USA, during October 28-31, 2024.

The 22 full papers presented in this volume were carefully reviewed and selected from 113 submissions.

They are grouped into the following topics: process modeling; advanced modeling languages; ontological modeling; domain and goal modeling; language models and conceptual modeling; applications of conceptual modeling.

Produktdetails

• Lecture Notes in Computer Science 15238
• Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-75871-3
• Seitenzahl: 476
• Erscheinungstermin: 27. Oktober 2024
• Englisch
• Abmessung: 235mm x 155mm x 26mm
• Gewicht: 715g
• ISBN-13: 9783031758713
• ISBN-10: 3031758714
• Artikelnr.: 71737208

Inhaltsangabe

.- Process Modeling.

.- Enhancing BERT Performance: Multi-Teacher Adversarial Distillation with Clean and Robust Guidance.

.- On the Task-specific Effects of Fragmentation in Modular Process Models.

.- A Universal Prompting Strategy for Extracting Process Model Information from Natural Language Text using Large Language Models.

.- Agent System Event Data: Concepts, Dimensions, Applications.

.- Advanced Modeling Languages.

.- Multi-Faceted Evaluation of Modeling Languages for Augmented Reality Applications - The Case of ARWFML.

.- Application of the Tree-of-Thoughts Framework to LLM-Based Domain Modeling.

.- ECQL: Towards Succinct and Extensible Modeling of Multi-model Query Results.

.- Ontological Modeling.

.- An Analysis of the Semantic Foundation of KerML and SysML.

.- Portions of Matter and their Existential Events: An ontology-based conceptual model.

.- Model-Driven Design and Generation of Training Simulators for Reinforcement Learning.

.- Domain and Goal Modeling.

.- Generating Secure Workflow Designs from Requirements Goal Models Using Patterns.

.- Modeling and Reasoning about Explanation Requirements using Goal Models.

.- Enhancing Domain Modeling with Pre-trained Large Language Models: An Automated Assistant for Domain Modelers.

.- Language Models and Conceptual Modeling.

.- How Are LLMs Used for Conceptual Modeling? An Exploratory Study on Interaction Behavior and User Perception.

.- Small, Medium, and Large Language Models for Text-to-SQL.

.- Establishing Traceability between Natural Language Requirements and Software Artifacts by Combining RAG and LLMs.

.- Applications of Conceptual Modeling.

.- GenACT: An Ontology based Temporal Web Data Generator.

.- SAQI: An Ontology based Knowledge Graph Platform for Social Air Quality Index.

.- Conceptual Framework for Designing Hippocratic APIs.

.- The Role-Artifact-Function Framework for Understanding Digital Identity Models.

.- Ontological Foundations of Resilience.

.- Conceptual modelling method for digital twins.