Advanced Information Systems Engineering : 34th International Conference, CAiSE 2022, Leuven, Belgium, June 6-10, 2022, Proceedings (Lecture Notes in Computer Science)

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Advanced Information Systems Engineering : 34th International Conference, CAiSE 2022, Leuven, Belgium, June 6-10, 2022, Proceedings (Lecture Notes in Computer Science)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 562 p.
  • 言語 ENG
  • 商品コード 9783031074714
  • DDC分類 005.1

Full Description

This book constitutes the refereed proceedings of the 34th International Conference on Advanced Information Systems Engineering, CAiSE 2022, which was held in Leuven, Belgium, during June 6-10, 2022.The 31 full papers included in these proceedings were selected from 203 submissions. They were organized in topical sections as follows: Process mining; sustainable and explainable applications; tools and methods to support research and design; process modeling; natural language processing techniques in IS engineering; process monitoring and simulation; graph and network models; model analysis and comprehension; recommender systems; conceptual models, metamodels and taxonomies; and services engineering and digitalization.

Contents

Process mining.- Decision Mining with Time Series Data Based on Automatic Feature Generation.- Inferring A Multi-Perspective Likelihood Graph from Black-Box Next Event Predictors.- Bootstrapping Generalization of Process Models Discovered From Event Data.- Learning Accurate Business Process SimulationModels from Event Logs via Automated Process Discovery and Deep Learning.- Multi-perspective Process Analysis: Mining the Association between Control Flow and Data Objects.- Sustainable and explainable applications.- Towards Greener Applications: Enabling Sustainable-aware Cloud Native Applications Design.- Towards Explainable Artificial Intelligence in Financial Fraud Detection: Using Shapley Additive Explanations to Explore Feature Importance.- Tools and methods to support research and design.- Systematic Literature Review Search Query Refinement Pipeline: Incremental Enrichment and Adaptation.- A model-driven approach for systematic reproducibility and replicability of data science projects.- The Aircraft and its Manufacturing System: From Early Requirements to Global Design.- Process modeling.- Causal Reasoning over Decisions in Process Models.- Crop Harvest Forecast via Agronomy-informed Process Modelling and Predictive Monitoring.- Guiding Knowledge Workers under Dynamic Contexts.- Natural language processing techniques in IS engineering.- Context Knowledge-aware Recognition of Composite Intents in Task-oriented Human-Bot Conversations.- Crowdsourcing syntactically diverse paraphrases with diversity-aware prompts and workflows.- A Subject-aware Attention Hierarchical Tagger for Joint Entity and Relation Extraction.- Process monitoring and simulation.- Estimating Activity Start Timestamps in the presence of Waiting Times via Process Simulation.- Updating prediction models for predictive process monitoring.- Multi-Model Monitoring Framework for Hybrid Process Specifications.- Graph and network models.- Mining valuable collaborations from event data using the Recency-Frequency-Monetary principle.- Querying temporal property graphs.- A Supervised Learning Community Detection Method Based on Attachment Graph Model.- Model analysis and comprehension.- Soundness of data-aware processes with arithmetic conditions.- Narration as a Technique to Improve Process Model Comprehension: Tell Me What I Cannot See.- Analyzing Enterprise Architecture Models by Means of the Meta Attack Language.- Recommender systems.- Enhancing Semantics-Driven Recommender Systems with Visual Features.- Assisting Mentors in Selecting Newcomers' Next Task in Software Product Lines: A Recommender System Approach.- Conceptual models, metamodels and taxonomies.- Towards Interoperable Metamodeling Platforms: The Case of Bridging ADOxx and EMF.- Services engineering and digitalization Situation Awareness for Autonomous Vehicles Using Blockchain-based Service Cooperation.- How Big Service and Internet of Services Drive Business Innovation and Transformation.- Time-Cost Tradeoffs for Composed Services.

 

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