Advanced information systems engineering : 34th International Conference, CAiSE 2022, Leuven, Belgium, June 6-10, 2022 : proceedings
著者
書誌事項
Advanced information systems engineering : 34th International Conference, CAiSE 2022, Leuven, Belgium, June 6-10, 2022 : proceedings
（Lecture notes in computer science, 13295）
Springer, c2022
- : [pbk.]
大学図書館所蔵 件 / 全1件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
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.
「Nielsen BookData」 より
