Web and big data Part 4
.- 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...
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| Weitere Verfasser: | , , , , , |
| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Singapore
Springer
2024
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| Schriftenreihe: | Lecture notes in computer science
14964 |
| Schlagworte: |
Algorithmen und Datenstrukturen
> Algorithms & data structures
> Angewandte Informatik
> Bildverarbeitung
> COMPUTERS / Computer Science
> COMPUTERS / Data Processing / Optical Data Processing
> COMPUTERS / Database Management / Data Mining
> COMPUTERS / Database Management / General
> COMPUTERS / Expert Systems
> COMPUTERS / Information Theory
> COMPUTERS / Programming / Algorithms
> Data Mining
> Data mining
> Databases
> Datenbanken
> Expert systems / knowledge-based systems
> Image processing
> Information technology: general issues
> Information theory
> Informationstheorie
> Konferenzschrift
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| Online Zugang: | Cover |
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| Zusammenfassung: | .- 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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| Beschreibung: | Literaturangaben |
| Beschreibung: | xviii, 512 Seiten Diagramme |
| ISBN: | 9789819772407 978-981-97-7240-7 |