Cooperative Information Systems (eBook, PDF)

30th International Conference, CoopIS 2024, Porto, Portugal, November 19-21, 2024, Proceedings
Redaktion: Comuzzi, Marco; Zhou, Zhangbing; Sellami, Mohamed; Grigori, Daniela

• Format: PDF

Produktbeschreibung

This book constitutes the refereed proceedings of the 30th International Conference on Cooperative Information Systems, CoopIS 2024, held in Porto, Portugal, during November 19-21, 2024. The 16 full papers, 11 short papers and 2 invited papers were carefully reviewed and selected from 78 submissions. They were organized in topical sections as follows: processes and human-in-the-loop; process analytics and technology; process improvement; knowledge graphs and knowledge engineering; predictive process monitoring; services and cloud; and short papers.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 412
• Erscheinungstermin: 13. Februar 2025
• Englisch
• ISBN-13: 9783031813757
• Artikelnr.: 73365178

Inhaltsangabe

.- Invited Speakers.
.- Business Models, Business Processes and Information Systems: A Dynamic Network View.
.- Machine Learning and Generative AI in BPM: Recent Developments and Emerging Challenges.
.- Processes and Human-in-the-loop.
.- Using Eye-Tracking to Detect Search and Inference During Process Model Comprehension.
.- Conversationally Actionable Process Model Creation.
.- Event Log Extraction for Process Mining Using Large Language Models.
.- Process Analytics and Technology.
.- All Optimal k-Bounded Alignments Using the FM-Index.
.- Unsupervised Anomaly Detection of Prefixes in Event Streams Using Online Autoencoders.
.- Autoencoder-Based Detection of Delays, Handovers and Workloads over High-Level Events.
.- Process Improvement.
.- SwiftMend: An Approach to Detect and Repair Activity Label Quality Issues in Process Event Streams.
.- Towards Fairness-Aware Predictive Process Monitoring: Evaluating Bias Mitigation Techniques.
.- Knowledge Graphs and Knowledge Engineering.
.- A User-Driven Hybrid Neuro-Symbolic Approach for Knowledge Graph Creation from Relational Data.
.- Assisted Data Annotation for Business Process Information Extraction from Textual Documents.
.- FleX: Interpreting Graph Neural Networks with Subgraph Extraction and Flexible Objective Estimation.
.- Predictive Process Monitoring.
.- Handling Catastrophic Forgetting: Online Continual Learning for next Activity Prediction.
.- A Decomposed Hybrid Approach to Business Process Modeling with LLMs.
.- Services and Cloud.
.- Self-Organising Approach to Anomaly Mitigation in the Cloud-to-Edge Continuum.
.- TALOS: Task Level Autoscaler for Apache Flink.
.- Automating Pathway Extraction from Clinical Guidelines: A Conceptual Model, Datasets and Initial Experiments.
.- Short Papers.
.- IML4DQ: Interactive Machine Learning for Data Quality with Applications in Credit Risk.
.- Optimizing B-trees for Memory-Constrained Flash Embedded Devices.
.- Predictive Process Approach for Email Response Recommendations.
.- Achieving Fairness in Predictive Process Analytics via Adversarial Learning.
.- Enhancing Temporal Knowledge Graph Reasoning with Contrastive Learning and Self-Attention Mechanisms.
.- Graph Convolution Transformer for Extrapolated Reasoning on Temporal Knowledge Graphs.
.- Collaboration Miner: Discovering Collaboration Petri Nets.
.- Discovering Order-Inducing Features in Event Knowledge Graphs.
.- LabelIT: A Multi-Cloud Resource Label Unification Tool.
.- Nala2BPMN: Automating BPMN Model Generation with Large Language Models.
.- TeaPie: A Tool for Efficient Annotation of Process Information Extraction Data.