Web and Big Data [electronic resource] : 8th International Joint Conference, APWeb-WAIM 2024, Jinhua, China, August 30 - September 1, 2024, Proceedings, Part IV / 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 ; 14964Editor: Singapore : Springer Nature Singapore : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: XVIII, 512 p. 150 illus., 132 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9789819772414Tema(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:
-- Database System and Query Optimization. -- SAM: A Spatial-aware Learned Index for Disk-Based Multi-dimensional Search. -- BIVXDB: A Bottom Information Invert Index to Speed up the Query Performance of LSM-tree. -- Dual-contrastive multi-view clustering under the guidance of global similarity and pseudo-label. -- A Powerful Local Search Method for Minimum Steiner Tree Problem. -- Federated and Privacy-Preserving Learning. -- FedOCD: A One-Shot Federated Framework for Heterogeneous Cross-Domain Recommendation. -- Efficient Updateable Private Set Intersection on Outsourced Datasets. -- Client Evaluation and Revision in Federated Learning: Towards Defending Free-Riders and Promoting Fairness. -- A Secure Dynamic Incentive Scheme for Federated Learning. -- A Data Synthesis Approach Based on Local Differential Privacy. -- Byzantine-Robust Aggregation for Federated Learning with Reinforcement Learning. -- Differential Privacy with Data Removal for Online Happiness Assessment. -- EPCQ: Efficient Privacy-preserving Contact Query Processing over Trajectory Data in Cloud. -- Parallel Secure Inference for Multiple Models based on CKKS. -- PrivRBFN: Building Privacy-Preserving Radial Basis Function Networks Based on Federated Learning. -- Robust Federated Learning with Realistic Corruption. -- Network, Blockchain and Edge computing. -- BTQoS: A Tenant Relationship-Aware QoS Framework for Multi-Tenant Distributed Storage System. -- ACMDS: An Anonymous Collaborative Medical Data Sharing Scheme Based on Blockchain. -- MTEC: A Multi-tier Blockchain Storage Framework using Erasure Coding for IoT Application. -- Maintaining Data Freshness in Multi-channel Multi-hop Wireless Networks. -- Proof of Run: A Fair and Sustainable Blockchain Consensus Protocol based on Game Theory in DApps. -- KTSketch: Finding k-persistent t-spread Flows in High-speed Networks. -- A Multi-agent Service Migration Algorithm for Mobile Edge Computing with Diversified Services. -- Dynamic Computation Scheduling for Hybrid Energy Mobile Edge Computing Networks. -- Anomaly Detection and Security. -- Malicious Attack Detection Method for Recommendation Systems Based on Meta-pseudo Labels and Dynamic Features. -- Detecting Camouflaged Social Bots through Multi-level Aggregation and Information Encoding. -- Deep Sarcasm Detection with Sememe and Syntax Knowledge. -- Enhancing Few-Shot Multi-Modal Fake News Detection through Adaptive Fusion. -- AGAE: Unsupervised Anomaly Detection for Encrypted Malicious Traffic. -- ColBetect: A Contrastive Learning Framework Featuring Dual Negative Samples for Anomaly Behavior Detection. -- Magnitude-Contrastive Network for Unsupervised Graph Anomaly Detection. -- Substructure-Guided Graph-level Anomaly with Attention-Aware Aggregation.
En: Springer Nature eBookResumen: The five-volume set LNCS 14961, 14962, 14963, 14964 and 14965 constitutes the refereed conference 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: Volume I: Natural language processing, Generative AI and LLM, Computer Vision and Recommender System. Volume II: Recommender System, Knowledge Graph and Spatial and Temporal Data. Volume III: Spatial and Temporal Data, Graph Neural Network, Graph Mining and Database System and Query Optimization. Volume IV: Database System and Query Optimization, Federated and Privacy-Preserving Learning, Network, Blockchain and Edge computing, Anomaly Detection and Security Volume V: Anomaly Detection and Security, Information Retrieval, Machine Learning, Demonstration Paper and Industry Paper.
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-- Database System and Query Optimization. -- SAM: A Spatial-aware Learned Index for Disk-Based Multi-dimensional Search. -- BIVXDB: A Bottom Information Invert Index to Speed up the Query Performance of LSM-tree. -- Dual-contrastive multi-view clustering under the guidance of global similarity and pseudo-label. -- A Powerful Local Search Method for Minimum Steiner Tree Problem. -- Federated and Privacy-Preserving Learning. -- FedOCD: A One-Shot Federated Framework for Heterogeneous Cross-Domain Recommendation. -- Efficient Updateable Private Set Intersection on Outsourced Datasets. -- Client Evaluation and Revision in Federated Learning: Towards Defending Free-Riders and Promoting Fairness. -- A Secure Dynamic Incentive Scheme for Federated Learning. -- A Data Synthesis Approach Based on Local Differential Privacy. -- Byzantine-Robust Aggregation for Federated Learning with Reinforcement Learning. -- Differential Privacy with Data Removal for Online Happiness Assessment. -- EPCQ: Efficient Privacy-preserving Contact Query Processing over Trajectory Data in Cloud. -- Parallel Secure Inference for Multiple Models based on CKKS. -- PrivRBFN: Building Privacy-Preserving Radial Basis Function Networks Based on Federated Learning. -- Robust Federated Learning with Realistic Corruption. -- Network, Blockchain and Edge computing. -- BTQoS: A Tenant Relationship-Aware QoS Framework for Multi-Tenant Distributed Storage System. -- ACMDS: An Anonymous Collaborative Medical Data Sharing Scheme Based on Blockchain. -- MTEC: A Multi-tier Blockchain Storage Framework using Erasure Coding for IoT Application. -- Maintaining Data Freshness in Multi-channel Multi-hop Wireless Networks. -- Proof of Run: A Fair and Sustainable Blockchain Consensus Protocol based on Game Theory in DApps. -- KTSketch: Finding k-persistent t-spread Flows in High-speed Networks. -- A Multi-agent Service Migration Algorithm for Mobile Edge Computing with Diversified Services. -- Dynamic Computation Scheduling for Hybrid Energy Mobile Edge Computing Networks. -- Anomaly Detection and Security. -- Malicious Attack Detection Method for Recommendation Systems Based on Meta-pseudo Labels and Dynamic Features. -- Detecting Camouflaged Social Bots through Multi-level Aggregation and Information Encoding. -- Deep Sarcasm Detection with Sememe and Syntax Knowledge. -- Enhancing Few-Shot Multi-Modal Fake News Detection through Adaptive Fusion. -- AGAE: Unsupervised Anomaly Detection for Encrypted Malicious Traffic. -- ColBetect: A Contrastive Learning Framework Featuring Dual Negative Samples for Anomaly Behavior Detection. -- Magnitude-Contrastive Network for Unsupervised Graph Anomaly Detection. -- Substructure-Guided Graph-level Anomaly with Attention-Aware Aggregation.

The five-volume set LNCS 14961, 14962, 14963, 14964 and 14965 constitutes the refereed conference 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: Volume I: Natural language processing, Generative AI and LLM, Computer Vision and Recommender System. Volume II: Recommender System, Knowledge Graph and Spatial and Temporal Data. Volume III: Spatial and Temporal Data, Graph Neural Network, Graph Mining and Database System and Query Optimization. Volume IV: Database System and Query Optimization, Federated and Privacy-Preserving Learning, Network, Blockchain and Edge computing, Anomaly Detection and Security Volume V: Anomaly Detection and Security, Information Retrieval, Machine Learning, Demonstration Paper and Industry Paper.

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