This six-volume set LNCS 15986-15991 constitutes the proceedings of the 30th International Conference on Database Systems for Advanced Applications, DASFAA 2025, held in Singapore, during May 2629, 2025.
The 136 full papers presented in this book together with 89 short papers were carefully reviewed and selected from 731 submissions.They cover topics such as

Part I- Machine Learning and Text.
Part II- Emerging Application; NLP and Spatial-Temporal.
Part III- Graph; Knowledge Graph.
Part V- Recommendation and Security & Privacy.
Part VI- Language Model; Industry Papers and Demo Papers.

Inhalt

.- Well-designed Query Optimization Based on Pattern Tree.
.- Separating Frozen Pages via Learning-based Recognition with ZNS SSD for Write Amplification Reduction in Database.
.- BlindChain: Keeping Query Privacy in Blockchain Out of Sight.
.- OmniQO: An Adaptive Framework for Integrating ML and Traditional Query Optimizers.
.- LASE: A Learned Spatial Index for Dynamic Workloads.
.- HiCHT: High-performance Compact Hash Table.
.- WorthyPar: A Workload-Aware Data Hybrid Partitioning Advisor with Deep Reinforcement Learning.
.- GAS-DBSCAN: A Grid-based Adaptive Sampling Method for DBSCAN Clustering under Skewed Data Distribution.
.- Learning Distance-Aware Space Partitions for Approximate Nearest Neighbor Search.
.- Perspective-based Multi-task Learning for Outlier Interpretation.
.- SELVA: A Reliable and Fast Selectivity Estimation Method for Query Plan Optimization in Video Analytics.
.- Transcending Conventional Binary Labels: Revamping Knowledge Tracing with VAE-Generated Image Representation.
.- Efficient Computation of k Representative Regret Minimization G-Skyline Groups.
.- MoEPlan: A Lazy Learned Query-Selection Optimizer via Mixture of Optimizer Experts.
.- Time-Optimal Route Planning for Non-Linear Recharging Electric Vehicles on Road Networks.
.- RAP: Random Projection is What You Need for Vertical Federated Learning.
.- VF-FD: Feature Deduplication for Vertical Federated Learning.
.- VHFed: A Two-Tier Vertical and Horizontal Federated Learning Framework for Enhanced Model Performance.
.- Heterogeneous FL via active-passive collaboration.
.- Information-agnostic Model Poisoning Attacks against Byzantine-robust Federated Learning.
.- A Diffusion-based Triple Embedding Model for User Identity Linkage across Social Networks.
.- Key Users Identification-based Heterogeneous Hypergraph for Group Recommendation.
.- PRIM: Encoding Propagation Probability and Role-Aware Representation for Influence Maximization.
.- Clustering-Guided Dynamic Social Network Graph Partitioning.
.- Retrieval-Based Multimodal Data Augmentation for Multimodal Information Extraction in Social Media.
.- KMMN: Knowledge Enhanced Multimodal Multi-grained Network for Fake News Detection.
.- Memory-Augmented Short Time Series Forecasting.
.- Dynamic Group Nearest Neighbor Group Query over Streaming Data.
.- Compress Time Series with Smaller Error Tolerances.
.- UniMixer: Unified Patch-Wise and Global Inter-Series Dependency Modeling for Multivariate Time Series Forecasting.
.- Dynamic Multiple Continuous Top-k Queries Over Streaming Data.
.- CausalScaler: A Causality-Driven Autoscaling Framework for the Cloud.
.- A Benchmark Dataset and Instruction Fine-Tuning Methods for Metaphorical Comprehension and Explanation.
.- MPPG: Pluggable Multi-Periodic Pattern-Guided Approach for Multivariate Time Series Anomaly Detection.