Web and Big Data [electronic resource] : 8th International Joint Conference, APWeb-WAIM 2024, Jinhua, China, August 30 - September 1, 2024, Proceedings, Part III / edited by Wenjie Zhang, Anthony Tung, Zhonglong Zheng, Zhengyi Yang, Xiaoyang Wang, Hongjie Guo.

Colaborador(es): Zhang, Wenjie [editor.] | Tung, Anthony [editor.] | Zheng, Zhonglong [editor.] | Yang, Zhengyi [editor.] | Wang, Xiaoyang [editor.] | Guo, Hongjie [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Lecture Notes in Computer Science ; 14963Editor: Singapore : Springer Nature Singapore : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: XVII, 515 p. 190 illus., 177 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9789819772384Tema(s): Big data | Data structures (Computer science) | Information theory | Application software | Image processing -- Digital techniques | Computer vision | Data mining | Big Data | Data Structures and Information Theory | Computer and Information Systems Applications | Computer Imaging, Vision, Pattern Recognition and Graphics | Data Mining and Knowledge DiscoveryFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 005.7 Clasificación LoC:QA76.9.B45Recursos en línea: Libro electrónicoTexto
Contenidos:
-- Spatial and Temporal Data. -- Temporalformer: A Temporal Decomposition Causal Transformer Network For Wind Power Forecasting. -- MSCFNet: A Multi-Scale Spatial and Channel Fusion Network for Geological Environment Remote Sensing Interpreting. -- TS-HCL: Hierarchical Layer-wise Contrastive Learning for Unsupervised Domain Adaptation on Time-Series. -- Dynamic-Static Fusion for Spatial-Temporal Anomaly Detection and Interpretation in Multivariate Time Series. -- MFCD:A deep learning method with fuzzy clustering for time series anomaly detection. -- Graph Neural Network. -- SBGMN: A Multi-View Sign Prediction Network for Bipartite Graphs. -- Product Anomaly Detection on Heterogeneous Graphs with Sparse Labels. -- Generic and Scalable Detection of Risky Transactions Using Density Flows: Applications to Financial Networks. -- Attributed Heterogeneous Graph Embedding with Meta-graph Attention. -- Automated Multi-scale Contrastive Learning with Sample-awareness for Graph Classification. -- CGAR: A Contrastive Graph Attention Residual Network for Enhanced Fake News Detection. -- GCH: Graph contrastive Learning with Higher-order Networks. -- LPRL-GCNN for Multi-Relation Link Prediction in Education. -- Multi-view Graph Neural Network for Fair Representation Learning. -- MERGE: Multi-View Relationship Graph Network for Event-Driven Stock Movement Prediction. -- Relation-Aware Heterogeneous Graph Neural Network for Fraud Detection. -- Graph Mining. -- Robust Local Community Search over Large Heterogeneous Information Networks. -- Community discovery in social network via dual-technique. -- CSGTM: Capsule Semantic Graph-Guided Latent Community Topics Discovery. -- Efficient (α, β, γ)-Core Search in Bipartite Graphs Based on Bi-triangles. -- Identifying Rank-happiness Maximizing Sets under Group Fairness Constraints. -- Reachability-Aware Fair Influence Maximization. -- Towards Efficient Heuristic Graph Edge Coloring. -- Tree and Graph based Two-Stages Routing for Approximate Nearest Neighbor Search. -- Unbiasedly Estimate Temporal Katz Centrality and Identify Top-K Vertices in Streaming Graph. -- Database System and Query Optimization. -- Gar++: Natural Language to SQL Translation with Efficient Generate-and-Rank. -- A Composable Architecture for Cloud Transactional DBMS. -- Computing Minimum Subset Repair On Incomplete Data. -- Flutist: Parallelizing Transaction Processing for LSM-tree-based Relational Database. -- Poplar: Partially-Ordered Parallel Logging for Lower Isolation Levels. -- Table Embedding Models Based on Contrastive Learning for Improved Cardinality Estimation.
En: Springer Nature eBookResumen: 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.
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-- Spatial and Temporal Data. -- Temporalformer: A Temporal Decomposition Causal Transformer Network For Wind Power Forecasting. -- MSCFNet: A Multi-Scale Spatial and Channel Fusion Network for Geological Environment Remote Sensing Interpreting. -- TS-HCL: Hierarchical Layer-wise Contrastive Learning for Unsupervised Domain Adaptation on Time-Series. -- Dynamic-Static Fusion for Spatial-Temporal Anomaly Detection and Interpretation in Multivariate Time Series. -- MFCD:A deep learning method with fuzzy clustering for time series anomaly detection. -- Graph Neural Network. -- SBGMN: A Multi-View Sign Prediction Network for Bipartite Graphs. -- Product Anomaly Detection on Heterogeneous Graphs with Sparse Labels. -- Generic and Scalable Detection of Risky Transactions Using Density Flows: Applications to Financial Networks. -- Attributed Heterogeneous Graph Embedding with Meta-graph Attention. -- Automated Multi-scale Contrastive Learning with Sample-awareness for Graph Classification. -- CGAR: A Contrastive Graph Attention Residual Network for Enhanced Fake News Detection. -- GCH: Graph contrastive Learning with Higher-order Networks. -- LPRL-GCNN for Multi-Relation Link Prediction in Education. -- Multi-view Graph Neural Network for Fair Representation Learning. -- MERGE: Multi-View Relationship Graph Network for Event-Driven Stock Movement Prediction. -- Relation-Aware Heterogeneous Graph Neural Network for Fraud Detection. -- Graph Mining. -- Robust Local Community Search over Large Heterogeneous Information Networks. -- Community discovery in social network via dual-technique. -- CSGTM: Capsule Semantic Graph-Guided Latent Community Topics Discovery. -- Efficient (α, β, γ)-Core Search in Bipartite Graphs Based on Bi-triangles. -- Identifying Rank-happiness Maximizing Sets under Group Fairness Constraints. -- Reachability-Aware Fair Influence Maximization. -- Towards Efficient Heuristic Graph Edge Coloring. -- Tree and Graph based Two-Stages Routing for Approximate Nearest Neighbor Search. -- Unbiasedly Estimate Temporal Katz Centrality and Identify Top-K Vertices in Streaming Graph. -- Database System and Query Optimization. -- Gar++: Natural Language to SQL Translation with Efficient Generate-and-Rank. -- A Composable Architecture for Cloud Transactional DBMS. -- Computing Minimum Subset Repair On Incomplete Data. -- Flutist: Parallelizing Transaction Processing for LSM-tree-based Relational Database. -- Poplar: Partially-Ordered Parallel Logging for Lower Isolation Levels. -- Table Embedding Models Based on Contrastive Learning for Improved Cardinality Estimation.

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.

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