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.
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.
.- 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.
.- 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.
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