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[null,"1.","Record Nr.",null,"UNISA996706481903316"]
[null,null,"Autore",null,"Li Jiajia"]
[null,null,"Titolo",null,"Web and Big Data : 9th International Joint Conference, APWeb-WAIM 2025, Shenyang, China, August 28–30, 2025, Proceedings, Part III / / edited by Jiajia Li, Richard Chbeir, Lei Li, Chuanyu Zong, Yanfeng Zhang, Mengxuan Zhang"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2026"]
[null,null,"Edizione",null,"[1st ed. 2026.]"]
[null,null,"Descrizione fisica",null,"1 online resource (0 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science, , 1611-3349 ; ; 16115"]
[null,null,"Disciplina",null,"005.73"]
[{"$nulls":4},"003.54"]
[null,null,"Soggetti",null,"Data structures (Computer science)"]
[{"$nulls":4},"Information theory"]
[{"$nulls":4},"Application software"]
[{"$nulls":4},"Image processing - Digital techniques"]
[{"$nulls":4},"Computer vision"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Big data"]
[{"$nulls":4},"Data Structures and Information Theory"]
[{"$nulls":4},"Computer and Information Systems Applications"]
[{"$nulls":4},"Computer Imaging, Vision, Pattern Recognition and Graphics"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Big Data"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"-- 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.  -- "]
[{"$nulls":4},"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."]
[null,null,null,"Sommario/riassunto","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 "]
[{"$nulls":4},"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."]