Buch, Englisch, 661 Seiten, Format (B × H): 155 mm x 235 mm
23rd International Conference, WISA 2026, Kunming, China, August 7–9, 2026, Proceedings, Part II
Buch, Englisch, 661 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: Lecture Notes in Computer Science
ISBN: 978-981-9286-88-1
Verlag: Springer
This book constitutes the refereed proceedings of the 23rd CCF Conference on Web Information Systems and Applications, WISA 2026, held in Kunming, China, during August 7-9, 2026.
The 152 full papers, 20 short papers and 8 demo papers presented in this book were carefully selected and reviewed from 571 submissions. These papers have been organized in the following topical sections:
Part I : Large Language Models, Agents and Retrieval-Augmented Generation,Temporal Analytics and Intelligent Decision-Making and Data Management and Graph Intelligence I,
Part II : Data Management and Graph Intelligence II,Knowledge Graphs, Recommendation and Intelligent Services,Multimodal Learning and Language Intelligence and Security, Privacy and Trustworthy Computing I.
Part III : Security, Privacy and Trustworthy Computing II, Computer Vision and Perceptual Intelligence ,AI-Enabled Information Systems and Applications and Demo Papers.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
.- Data Management and Graph Intelligence II
.- GLIA: Graph-Level Information Augmentation for High-Degree Graphs.
.- FPGA Acceleration for Graph Computing: Architectures, Techniques, and Challenges.
.- Reliability-Aware Dual-Contrastive Attention Fusion for Multi-View Clustering.
.- RippleSC: Learned Incremental Subgraph Counting with Ripple-Based Substructure Extraction.
.- Mixed-Reconstruction Adaptive-Depth Variational Graph Attention Auto-Encoders for Link Prediction.
.- Enhancing Text-to-SQL with Automated Chain-of-Thought Data Generation and Pipeline-Based Multi-Stage Query Selection.
.- Knowledge Graphs, Recommendation and Intelligent Services
.- HCSRec: Multi-Scale Perception and Hierarchical Capsule Contrastive Learning for Sequential Recommendation.
.- DualLink: Dual-Stage Schema Linking via Exploration and Reconsideration.
.- A Knowledge Graph Completion Method Based on Dual-View Potential Positive Mining and Adaptive Weighted Training.
.- RevBERT: A Variational Compressed Relation Embedding Model Based on the BERT Framework.
.- TEMEA: Topology Enhanced Multimodal Entity Alignment.
.- AERec: Personalized Aspect-instructed Explainable Recommendation using Large Language Models.
.- Reliability Matters: A Reliable Transfer Framework for Universal Cross-Domain Recommendation.
.- Signed-Graph Recommendation as Structural Consistency Maximization.
.- RSRA: Relation Semantic-Aware Rotation Attention Mechanism for Knowledge Graph Enhanced Recommendation.
.- OrthoGLF: Capacity-Aware Orthogonal Graph-Language Fusion for Sequential Recommendation.
.- LLM Empowered Knowledge Graph Reinforcement Learning for Recommendation.
.- Popularity-Aware Preference Optimization for Balanced Long-Tail LLM Recommendation.
.- Enhancing Cybersecurity Knowledge Graphs with TTPs Ontology Semantic Constraints: From Link Prediction to Intelligent Penetration Testing.
.- CAARec: Consistency-Aware Adaptive Alignment for Multimodal Item Representation Learning in Recommendation.
.- MDA-Rec: Multi-Agent Data Augmentation and Spectrum-Aware Learning for Multimodal Recommendation.
.- Explaining Dynamic Causality in Temporal Recommendation.
.- DSSRec: Signed Preference Modeling with Negative Interactions Masking.
.- Caco-Ranker: Candidate-aware Contextualized and Calibrated Ranking for Document Re-ranking.
.- KGHoney: A Knowledge Graph-Driven Framework for Honeypoint Placement in Deception Defense System.
.- Emotion-Aware POI Category Recommendation Based on Emotional Experience Perception.
.- SALC: Structure-aware and Length-adaptive Contrastive Learning for Short POI Sequence Recommendation.
.- SDFR-KGC: Structure Denoising and Feature Refinement for Knowledge Graph Completion.
.- Multimodal Learning and Language Intelligence
.- Cross-Modal Fusion of Structural and Semantic Features for Robust Malware Analysis.
.- Multi-Modal Graph Neural Network for ADHD Prediction: Integrating Neuroimaging, Demographics, and Clinical Data.
.- DERA: Dynamic Expert Routing Architecture for Multi-Source Heterogeneous Fake News Video Detection.
.- HiFi: Hierarchical Fusion-based Multi-Modal Knowledge Graph Completion with Structural Attention Generation.
.- PMDA-DAMMFND: A Prototype Memory-Guided Framework for Multi-Domain Multimodal Fake News Detection.
.- FAME: Fusion Adaptation and Modality Excitation for Robust Multimodal Sentiment Analysis.
.- Domain-Aware Routing for Multi-Domain Misinformation Detection.
.- CogMESE: A Cognitive-inspired Multimodal Entity Set Expansion Model.
.- CogMA: A Cognitive-inspired Multi-scale Perceptual Modality Alignment Model.
.- Entity Description Generation: A Textual Completion Task for Multimodal Knowledge Graphs.
.- NODE: A Non-linear Modality State Dynamics Evolution Network for Multimodal Emotion-Cause Pair Extraction.
.- Topological Prototype Learning for Robust Multimodal Sentiment Analysis under Missing Modalities.
.- Graph-Aware Unsupervised Fusion Hashing for Remote Sensing Cross-Modal Retrieval.
.- SportMM-LT: A Single-Hop Multimodal Benchmark for Long-Tail Knowledge in Sports.
.- From Semantic Bridge to Feature Purification: A Unified Framework for Multimodal Relation Extraction.
.- WaveSE-GAN: A Physics-Guided Lightweight Speech Enhancement Network with Explicit Wave Propagation and Interference Modeling.
.- A Knowledge-Enhanced Planarized Representation for Relation Extraction.
.- Reasoning and Self-Reflection for LLM-based Structured Event Extraction.
.- A Modular Knowledge-Aware Framework for Cyber Threat Intelligence Named Entity Recognition.
.- SGSpan: Super-Node Guided Sparse Graph Attention for Continual Span-Based Named Entity Recognition.
.- AMR Compressed and Explicit Relation-Enhanced Graph Relation Prediction Model for Event Argument Extraction.
.- CDAR: Confidence-Aware Distillation with Hierarchical Adaptive Routing for Multimodal Entity and Relation Extraction.
.- Security, Privacy and Trustworthy Computing I
.- A Cross-domain Graph Privacy-Preserving Method Based on Multi-Agent Collaboration and Stratified Sampling Strategies.
.- LINET: Line Number Injection for Enhanced Trustworthiness in LLM-based Vulnerability Localization.
.- A Secure Blockchain-based Cross-Heterogeneous Domain Data Sharing Method.
.- A DDoS Attack Detection Method Based on Concise-former.
.- A Multilayer Network Intrusion Detection Method for Hyperledger Fabric.
.- LDP-DGC: Degree-Consistent Directed Graph Synthesis under Local Differential Privacy with Community Preservation.
.- EdgeDefend: A Systematic Edge Defense Framework Against LLM-driven Automated Penetration Testing for Microservices.
.- EGridLedger: Blockchain-Enhanced Evidence Governance for DDRE-33 Renewable Scenario Analytics.
.- EdgeGuard: Cloud-Edge Collaborative Dual-Stage Unsupervised Learning for Line-Rate Edge Intrusion Detection.
