Advances in Databases and Information Systems
Description
This book constitutes the proceedings of the 29th European Conference on Advances in Databases and Information Systems, ADBIS 2025, which took place in Tampere, Finland, during September 23-26, 2025.
The 14 full papers included in this proceedings book were carefully reviewed and selected from 66 submissions. The book also contains 4 tutorial papers. The selected papers span a large spectrum of topics in the broader field of data management focusing on Query Optimization, Explainable AI, Entity Resolution and Integration, Data and Machine Learning, Spatio-Temporal and Graph Data, and Data Sharing and Synthesis.
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Content
.- Keynote Talk.
.- Data Quality (Assessment) in the Age of AI.
.- Query Optimization.
.- Independence Rules: Analysis of Nine Simple Cardinality Estimators and Their Impact on Plan Quality.
.- Vector Database Benchmarking: A Face Retrieval Use Case.
.- PUL: Pre-load in Software for Caches Wouldn't Always Play Along.
.- Explainable AI.
.- Responsible AI: Training deep learning model efficiently.
.- Exploring local feature influences with Hierarchical Explanation Trees.
.- Towards Trace Variant Explainability.
.- Evaluating Knowledge Generation and Self-Refinement Strategies for LLM-based Column Type Annotation.
.- Entity Resolution & Integration.
.- LSBlock: A Hybrid Blocking System Combining Lexical and Semantic Similarity Search for Record Linkage.
.- Evaluating Quality of Disparate Data Sources: A Discord-Driven Approach.
.- Pasteur: Scaling Privacy-aware Data Synthesis.
.- Generating Semantically Enriched Mobility Data from Travel Diaries.
.- Data & Machine Learning.
.- Learning a Distance for the Stratification of Patients with Amyotrophic Lateral Sclerosis.
.- Designing Efficient and Scalable Substructure Discovery Algorithms for Multilayer Networks.
.- Bitemporal Property Graphs: dealing with both valid and transaction time.
.- Tutorials.
.- Graph Analytics for Bridging Human and Data Sciences.
.- Data Warehousing: The Industrial Perspective.
.- Vector Representations of Multi-Modal Data.
.- Utilizing Quantum Computing to Improve the Quality of Data.
