Sellami / Vidal / van Dongen Cooperative Information Systems

29th International Conference, CoopIS 2023, Groningen, The Netherlands, October 30–November 3, 2023, Proceedings
Erscheinungsjahr 2023
ISBN: 978-3-031-46846-9
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 508 Seiten

Reihe: Computer Science

This book constitutes the refereed proceedings of the 29th International Conference on Cooperative Information Systems, CoopIS 2023, held in Groningen, The Netherlands, during October 30–November 3, 2023. The 21 regular papers and 10 work-in-progress papers included in this book were carefully reviewed and selected from 100 submissions. They were organized in topical sections as follows: Knowledge Engineering; Deployment and Migration in CISs; Security and Privacy in CISs; Process Modeling; Process Analytics; Human Aspects and Social Interaction in CISs; and Work in Progress.

Zielgruppe

Research

Autoren/Hrsg.

Sellami, Mohamed

Vidal, Maria-Esther

van Dongen, Boudewijn

Gaaloul, Walid

Panetto, Hervé

Inhaltsverzeichnis

Knowledge Engineering .- Enhancing Fairness and Accuracy in Machine Learning through Similarity Networks.- Considering Vocabulary Mappings in Query Plans for Federations of RDF Data Sources.- AIS – a Metric for assessing the Impact of an Influencer’s Twitter Activity on the Price of a Cryptocurrency.-  Deployment and Migration in CISs .- Managing the Variability of Component Implementations and Their Deployment Configurations Across Heterogeneous Deployment Technologies.- Adaptive Multi-Agent System for Dynamic Clustering Applied to Itineraries Regularities and Traffic Prediction.- Double Deep Q-Network-based Time and Energy-efficient Mobility-aware Workflow Migration Approach.-  Security and Privacy in CISs .- Decentralized and Autonomous Key Management for Open Multi-Agent Systems of Embedded Agents.- An Empirical Study on Socio-technical Modeling for Interdisciplinary Privacy Requirements.- Enhancing Workflow Security in Multi-Cloud Environments through Monitoring and Adaptation upon Cloud Service and Network Security Violations.-  Process Modeling .- Beyond Rule-based Named Entity Recognition and Relation Extraction for Process Model Generation from Natural Language Text.- LABPMN: Location-Aware Business Process Modeling and Notation.- On the Semantic Transparency of Declarative Process Models: The Case of Constraints.-  Process Analytics .- Discovering Guard Stage Milestone models through hierarchical clustering.- Discovery of Workflow Patterns - A Comparison of Process Discovery Algorithm.- From Process Mining Insights to Process Improvement: All Talk and No Action?.- Rectify Sensor Data in IoT: A Case Study on Enabling Process Mining for Logistic Process in an Air Cargo Terminal.- Using Process Mining for Face Validity Assessment in Agent-based Simulation Models: An Exploratory Case Study.-  Human Aspects and Social Interaction in CISs .- Towards Scaling External Feedback for Early-Stage Researchers: A survey study.- Social Network Mining from Natural Language Text and Event Logs for Compliance Deviation Detection.- Learning Hierarchical Robot Skills Represented by Behavior Trees from Natural Language.- Relating Context and Self Awareness in the Internet of Things.-  Work in Progress (WIP) Papers .- BAnDIT: Business Process Anomaly Detection in Transactions.- Resource-Driven Process Manipulation: Modeling Concepts and ValidAllocations.- Graph Collaborative Filtering and Data Augmentation Strategies in Dual-Target CDR.- Clustering Raw Sensor Data in Process Logs to Detect Data Streams.- Comparing the Performance of GPT-3 with BERT for Decision Requirements Modeling.- A Requirements Study on Model Repositories for Digital Twins in Construction Engineering.- Joint Dynamic Resource Allocation and Trajectory Optimization for UAV-Assisted Mobile Edge Computing in Internet of Vehicles.- Towards an Improved Unsupervised Graph-based MRI Brain Segmentation Method.- User-friendly exploration of highly heterogeneous data lakes.- Optimizing hospital patient flow by predicting aftercare requests from fuzzy time series.