Database Systems for Advanced Applications
Springer Verlag, Singapore
978-981-95-4148-5 (ISBN)
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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.
.- 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.
| Erscheinungsdatum | 29.11.2025 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science |
| Zusatzinfo | XX, 483 p. |
| Verlagsort | Singapore |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | Graph • Knowledge graph • Language Model • machine learning • NLP • privacy • Recommendation • security • Time Series |
| ISBN-10 | 981-95-4148-4 / 9819541484 |
| ISBN-13 | 978-981-95-4148-5 / 9789819541485 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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