TY  - BOOK
AU  - Zhang,Wenjie
AU  - Tung,Anthony
AU  - Zheng,Zhonglong
AU  - Yang,Zhengyi
AU  - Wang,Xiaoyang
AU  - Guo,Hongjie
ED  - SpringerLink (Online service)
TI  - Web and Big Data: 8th International Joint Conference, APWeb-WAIM 2024, Jinhua, China, August 30 - September 1, 2024, Proceedings, Part II 
T2  - Lecture Notes in Computer Science,
SN  - 9789819772353
AV  - QA76.9.B45 
U1  - 005.7 23
PY  - 2024///
CY  - Singapore
PB  - Springer Nature Singapore, Imprint: Springer
KW  - Big data
KW  - Data structures (Computer science)
KW  - Information theory
KW  - Application software
KW  - Image processing
KW  - Digital techniques
KW  - Computer vision
KW  - Data mining
KW  - Big Data
KW  - Data Structures and Information Theory
KW  - Computer and Information Systems Applications
KW  - Computer Imaging, Vision, Pattern Recognition and Graphics
KW  - Data Mining and Knowledge Discovery
N1  -  -- Recommender System.  -- Hierarchical Review-based Recommendation with Contrastive Collaboration.  -- Adaptive Augmentation and Neighbor Contrastive Learning for Multi-Behavior Recommendation.  -- Automated Modeling of Influence Diversity with Graph Convolutional Network for Social Recommendation.  -- Contrastive Generator Generative Adversarial Networks for Sequential Recommendation.  -- Distribution-aware Diversification for Personalized Re-ranking in Recommendation.  -- KMIC: A Knowledge-aware Recommendation with Multivariate Intentions Contrastive Learning.  -- Logic Preference Fusion Reasoning on Recommendation.  -- MHGNN: Hybrid Graph Neural Network with Mixers for Multi-interest Session-aware Recommendation.  -- Mixed Augmentation Contrastive Learning for Graph Recommendation System.  -- Noise-Resistant Graph Neural Networks for Session-based Recommendation.  -- S2DNMF: A Self-supervised Deep Nonnegative Matrix Factorization Recommendation Model Incorporating Deep Latent Features of Network Structure.  -- Self-Filtering Residual Attention Network based on Multipair Information Fusion for Session-Based Recommendations.  -- TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback.  -- VM-Rec: A Variational Mapping Approach for Cold-start User Recommendation.  -- Knowledge Graph.  -- Matching Tabular Data to Knowledge Graph based on Multi-level Scoring Filters for Table Entity Disambiguation.  -- Complex Knowledge Base Question Answering via Structure and Content Dual-driven Method.  -- EvoREG: Evolutional Modeling with Relation-Entity Dual-Guidance for Temporal Knowledge Graph Reasoning.  -- Federated Knowledge Graph Embedding Unlearning via Diffusion Model.  -- Functional Knowledge Graph Towards Knowledge Application and Data Management for General Users.  -- Hospital Outpatient Guidance System Based On Knowledge Graph.  -- TOP: Taxi Destination Prediction Based on Trajectory Knowledge Graph.  -- Type-based Neighborhood Aggregation for Knowledge Graph Alignment.  -- An Aggregation Procedure Enhanced Mechanism for GCN-based Knowledge Graph Completion Model by Leveraging Condensed Sampling and Attention Optimization.  -- Spatial and Temporal Data.  -- Capturing Fine and Coarse Grained User Preferences with Dual-Transformer for Next POI Recommendation.  -- Enhancing Spatio-Temporal Semantics with Contrastive Learning for Next POI Recommendation.  -- Distinguish the Indistinguishable: Spatial Personalized Transformer for Traffic Flow Forecast.  -- Meeting Pattern Detection from Trajectories in Road Network.  -- Speed Prediction of Multiple Traffic Scenarios with Local Fluctuation.  -- ST-TPFL: Towards Spatio-Temporal Traffic Flow Prediction Based on Topology Protected Federated Learning.  -- A Context-aware Distance Analysis Approach for Time Series.  -- Dual-view Stack State Learning Network for Attribute-based Container Location Assignment.  -- Efficient Coverage Query over Transition Trajectories
N2  - The five-volume set LNCS 14961, 14962, 14963, 14964 and 14965 constitutes the refereed proceedings of the 8th International Joint Conference on Web and Big Data, APWeb-WAIM 2024, held in Jinhua, China, during August 30-September 1, 2024. The 171 full papers presented in these proceedings were carefully reviewed and selected from 558 submissions. The papers are organized in the following topical sections: Part I: Natural language processing, Generative AI and LLM, Computer Vision and Recommender System. Part II: Recommender System, Knowledge Graph and Spatial and Temporal Data. Part III: Spatial and Temporal Data, Graph Neural Network, Graph Mining and Database System and Query Optimization. Part IV: Database System and Query Optimization, Federated and Privacy-Preserving Learning, Network, Blockchain and Edge computing, Anomaly Detection and Security Part V: Anomaly Detection and Security, Information Retrieval, Machine Learning, Demonstration Paper and Industry Paper
UR  - http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-981-97-7235-3
ER  -