Buch, Englisch, 701 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1077 g
9th International Joint Conference, APWeb-WAIM 2025, Shenyang, China, August 28-30, 2025, Proceedings, Part III
Buch, Englisch, 701 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1077 g
Reihe: Lecture Notes in Computer Science
ISBN: 978-981-955718-9
Verlag: Springer
The four-volume set LNCS constitutes the refereed proceedings of the 9th International Joint Conference on Web and Big Data, APWeb-WAIM 2025, held in Shenyang, China, during August 28–30, 2025.
The 136 full papers and 15 short papers presented in these proceedings were carefully reviewed and selected from 472 submissions. The papers are organized in the following topical sections:
Part I: Data Mining I; Machine Learning I; Information Retrieval and Knowledge Management I; Graph Data Management andAnalytics I; Complex Data Management.
Part II: Complex Data Management; Spatial and Temporal Data Management; Data Privacy and Trusted AI; Data Management on New Hardwares; Query Processing and Optimization; Data Mining II.
Part III: Data Mining II; Machine Learning II; Information Retrieval and Knowledge Management II; Graph Data Management andAnalytics II; Big Data Management.
Part IV: Big Data Management; LLM for Data Management; Information Retrieval; Demonstration Paper; Industry Paper.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
- Mathematik | Informatik EDV | Informatik Angewandte Informatik
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
Weitere Infos & Material
.- Data Mining II.
.- TimeMultiformer: Attention-Based Collaborative Feature and Temporal Dependencies Learning for
Multivariate Time Series Imputation.
.- Heterogeneous Graph-Enhanced Temporal Prediction withAdaptive Monitoring for Industrial Chain
Data.
.- Finding Maximum Common Subgraphs Efficiently Through Dynamic Bidirectional Vertex Selection.
.- TD-LTNet: Temporal-Decay LSTM-Transformer Network for Mobile Video QoE Prediction.
.- FACKT:AFault-Aware Model for Code Knowledge Tracing.
.- UCPM-CPI:AUnited Co-location Pattern MiningAlgorithm Based on Correlated Participation Index.
.- Machine Learning II.
.- ACross-modal Fusion Method for Short Video Fake News Detection via MambaFormer.
.- ALightweight Pavement Defect Detection Method Based on Multi-BranchAttention with Contextual
Guidance.
.- A Hierarchical Reinforcement Learning Method based on Decision Frequency and Internal Reward
Mechanism.
.- ASoluble Solids Content Prediction Method for Blueberries Based on Differential Enhancement and
Multi-Scale Feature Fusion.
.- MedDPA: Multi-Scale Decomposition and Prototype-based ChannelAggregation for Medical Time
Series Classification.
.- Knowledge Graph and Hypergraph Enabled Semantic Modeling for Dual-Intent Recommendation.
.- GK-SMOTE:AHyperparameter-free Noise-Resilient Gaussian KDE-Based OversamplingApproach.
.- Robust Ensemble Learning via t-Tilted Loss: ANoise-Resistant Framework.
.- A Multi-Scale Dilated Convolution model with Edge Optimization for Crack Detection.
.- A DeepReinforcement Learning Framework for Denial Constraint Discovery.
.- Information Retrieval and Knowledge Management II.
.- Generating Difficulty Controllable Multiple-Choice Question By Iteratively Guiding The Large
Language Model.
.- Research on a multi-modal entity alignment method based on neighborhood matching.
.- Multi-Granularity Knowledge Graph EntityAlignment via Semantic Clustering and Dynamic
Collaborative Projection.
.- MNS-EA:AMixedNegative Sampling-based EntityAlignment Model.
.- Improving Continual Relation Extraction via Parameter Regularization and Dynamic Memory.
.- MultiRelE: Multi-relation Knowledge Graph Embedding Model.
.- LE2C: LLM-Enhanced Event Evolutionary Graph for Explainable Classification.
.- Discrete Channel Mapping in Knowledge Distillation.
.- Uncertainty-Aware Semantic Decoding for LLM-Based Sequential Recommendation.
.- Dual-StreamAdaptive Retrieval and HierarchicalAgent Collaboration for Document Visual QA.
.- Retrieval and Distill: ATemporal Data Shift-Free Paradigm for Online Recommendation System.
.- Retrieval-based Knowledge Consistency Validation for Fake News Detection.
.- Graph Data Management andAnalytics II.
.- DCS-GCN:ADual-Channel Social Graph Convolutional Network for Recommendation.
.- DED: Integrating Degree Entropy and Dynamic Delay Mechanisms for Influence Maximization in Multilayer Networks.
.- ComIVY: Community-Driven Budgeted Influence Maximization via IVY Optimization.
.- Enhancing Partial Evaluation Subgraph Matching Through Vertex Hotness Caching.
.- Fetan: Enhancing Few-Shot Classification on Text-Attributed Graphs with In-Context Learning of LLMs.
.- Graph Contrastive Anomaly Detection Based on Beta Wavelet Multi-GNNs.
.- Adaptive Graph Contrastive Learning for Blockchain Smart Contract Vulnerability Detection.
.- CPGCN:Evolutionary Relationship Mining Framework for Ethnic Costume Elements.
.- Shilling Attacks on GNN-based Recommender Systems with Graph Contrastive Learning.
.- Big Data Management.
.- DC-Storage: AFast Permissioned IoT Blockchain Storage with Decoupled Index.
.- zkHARPS:ADecentralized Method for Cross-Chain Identity Aggregation and Privacy Proof.
.- FLAR: Fibonacci-assisted Lightweight Anonymous RevocableAuthentication Scheme in Industrial
Internet of Things.
.- RL-ABO:Adaptive Blockchain Control Parameter Optimization Method Based on Reinforcement
Learning.
.- ByzTierFL:ATieredApproach to Byzantine Robust and Decentralized Federated Learning.
.- Root Cause Localization Through Holistic Fault Propagation Perspective for Cloud-native Systems.
