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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 26 29, 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 V- Recommendation and Security & Privacy.
Part VI- Language Model; Industry Papers and Demo Papers.
List of contents
.- Recommendation.
.- Hypergraph Enhanced Knowledge Tree Prompt Learning for Next-Basket Recommendation.
.- MHGCP:Multi-View Heterogeneous Graph with Cross-View Projection for Recommendation.
.- Towards Scenario-adaptive User Behavior Modeling for Multi-scenario Recommendation.
.- Leave No One Behind: Enhancing Diversity While Maintaining Accuracy in Social Recommendation.
.- Counterfactual Path Augmentation for Reinforcement Reasoning in Explainable Recommendation.
.- Adaptive Personalized Federated Recommendation with Global Knowledge Distillation.
.- FHCF: Fully-Hyperbolic Symmetric Graph Learning for Collaborative Filtering.
.- UGDA: A Unified Graph-based Method with Domain-specific Adaptation for Multi-domain Recommendation.
.- Self-supervised Hierarchical Representation for Medication Recommendation.
.- Self-Supervised Dual Graph and Intention Association for Session-based Recommendation.
.- Exercise Recommendation Based on Feature-Aligned Knowledge Tracing.
.- Joint User and Item Prototype Alignment for Cross-Platform Recommendation.
.- Diffusion Multi-Behavior Recommender Model .
.- HHGCN-DrugRec: Hierarchical HyperGraph Convolution Network for Drug Combination Recommendation.
.- Emotion-based Conversational Recommendation by Inferring Implicit Users Preferences from their Subjective Claims.
.- CDIVR: Cognitive Dissonance-aware Interactive Video Recommendation.
.- Modeling Personalized Short-term and Periodic Long-term Preferences for Enhanced Next POI Recommendations.
.- DRE: Generating Recommendation Explanations by Aligning Large Language Models at Data-level.
.- Towards Unified Modeling for Positive and Negative Preferences in Sign-aware Recommendation.
.- Alignment-Uniformity Aware Feature Representation Learning for CTR Prediction.
.- Diffusion Based Data Augmentation for Multi-behavior Sequential Recommendation.
.- Semantic Gaussian Mixture Variational Autoencoder for Sequential Recommendation*.
.- Personalized Education with Ranking Alignment Recommendation.
.- HierLLM: Hierarchical Large Language Model for Question Recommendation.
.- Comprehensive Interest Modeling and Relational Mining for Multi-modal Recommendation.
.- Demand-oriented Route Recommendation for Shared Mobility Services.
.- CoCoB: Adaptive Collaborative Combinatorial Bandits for Online Recommendation.
.- KG-TS: Knowledge Graph-driven Thompson Sampling for Online Recommendation.
.- Efficient Noise-reducing Neural Network for Cross-Domain Sequential Recommendation.
.- Bridging RDF Knowledge Graphs with Graph Neural Networks for Semantically-Rich Recommender Systems.
.- Security & Privacy.
.- Lattice-based Forward Secure Certificateless Encryption Scheme for Cloud Data Management.
.- Logarithmic-size Lattice-based Linkable Ring Signature for Cloud Data Management.
.- CyberLLM: Enable Mapping CVE to Tactics and Techniques of Cyber Threats via LLM.
.- Privacy-preserving Multi-Dimensional Range Query Optimization Across Multiple Sources.
.- Decoupled Self-Knowledge Distillation Makes Differentially Private Deep Learning Stronger.
.- PriExRec: Defending Against Membership Inference Attacks in Federated Recommendation with Explicit Feedback.
.- OPOM: The Ordinal and Parallel Optimization Method of Spark multi-query applications.
.- Enabling Efficient and Authenticated Trajectory Similarity Retrieval on Blockchain-assisted Cloud.
.- InC: A Vertical Federated Learning Framework with Multiple Noisy Labels.
.- Breaking Free from Label Limitations: A Novel Unsupervised Attack Method for Graph Classification.
.- TSALockMark: An Asymmetric and Robust Watermarking Scheme for Relational Databases with Distortion Constraints.
.- Towards Confidential and Efficient LLM Inference with Dual Priva
Summary
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 26–29, 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 V- Recommendation and Security & Privacy.
Part VI- Language Model; Industry Papers and Demo Papers.
