UID:
almahu_9949985931502882
Umfang:
XVI, 412 p. 162 illus., 136 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2025.
ISBN:
9783031813757
Serie:
Lecture Notes in Computer Science, 15506
Inhalt:
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. .
Anmerkung:
-- 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.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783031813740
Weitere Ausg.:
Printed edition: ISBN 9783031813764
Sprache:
Englisch
DOI:
10.1007/978-3-031-81375-7
URL:
https://doi.org/10.1007/978-3-031-81375-7
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