Database Systems for Advanced Applications: 30th International Conference, DASFAA 2025, Singapore, Singapore, May 26–29, 2025, Proceedings, Part V(15990 Lecture Notes in Computer Science)

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.

Table 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 Privacy Protection. .- ECPIR: Efficient and Controllable Privacy-Preserving Image Retrieval in Cloud-Assisted System. .- Privacy-preserving Image Generation Based on Self-Attention.