Knowledge Science, Engineering and Management : 17th International Conference, KSEM 2024, Birmingham, UK, August 16–18, 2024, Proceedings, Part IV / / edited by Cungeng Cao, Huajun Chen, Liang Zhao, Junaid Arshad, Taufiq Asyhari, Yonghao Wang

• Autore: Cao Cungeng
• Pubblicazione: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
• Edizione: 1st ed. 2024.
• Descrizione fisica: 1 online resource (465 pages)
• Disciplina: 006.3
• Soggetto topico: Artificial intelligence; Computer engineering; Computer networks; Computers; Information technology - Management; Social sciences - Data processing; Application software; Artificial Intelligence; Computer Engineering and Networks; Computing Milieux; Computer Application in Administrative Data Processing; Computer Application in Social and Behavioral Sciences; Computer and Information Systems Applications
• Altri autori: ChenHuajun ZhaoLiang ArshadJunaid AsyhariTaufiq WangYonghao
• Nota di contenuto: -- Emerging Technology. -- Integrated geologic terms and dual model for Chinese geological word segmentation. -- Random Virtual Embeddings Bootstrap High-degree Item Diffusion for Recommendation. -- Contrastive Learning for Money Laundering Detection: Node- Subgraph-Node Method with Context Aggregation and Enhancement Strategy. -- GCCR: GAT-Based Category-aware Course Recommendation. -- Exploring Word Composition Knowledge In Language Usages. -- L2R-Nav: A Large Language Model-Enhanced Framework for Robotic Navigation. -- Adversarial attacks on Large Language Models. -- Enhancing Question Embedding with Relation Chain for Multi-hop KGQA. -- IIU: Independent Inference Units for Knowledge-based Visual Question Answering. -- Research on Blockchain-Based Trustworthy Data Sharing and Privacy Data Protection Mechanism. -- A Hierarchical Neural Task Scheduling Algorithm in The Operating System of Neuromorphic Computers. -- Efficient Data Asset Right Provenance for Data Asset Trading Based on Blockchain. -- CGCL: A Novel Collaborative Graph Contrastive Learning Network for Chinese NER. -- Scalable attack on graph data by important nodes. -- WaveSegNet: Wavelet Transform and Multi-Scale Focusing Network for Scrap Steel Segmentation. -- Recommendation Algorithm Based on Refined Knowledge Graphs and Contrastive Learning. -- Enhancing Pet Health Record Security through RSA-Encrypted NFTs and Smart Contracts on the Blockchain. -- A Blockchain-Based Secure ADS-B System. -- An Emotion-Aware Human-Computer Negotiation Model Powered by Pretrained Language Model. -- Feature Re-enhanced Meta-Contrastive Learning for Recommendation. -- ANGCN:Adaptive Neighborhood-awareness for Recommendation. -- The study of named entity identification in Chinese electronic medical records based on multi-tasking. -- A Comparative Study of Different Pre-trained Language Models for Sentiment Analysis of Human-Computer Negotiation Dialogue. -- Integrating Blockchain and RSA-Encrypted NFTs for Enhanced Digital Knowledge Management. -- An Effective RSP Data Sampling Algorithm. -- Rationality of Thought Improves Reasoning in Large Language Models. -- NFTMosaic: Piecing Together Assets in a Unified Blockchain Token. -- Global Context Enhanced Multi-Granularity Intent Networks for Session-based Recommendation. -- Enhancing Electoral Integrity: A Comprehensive Study of Blockchain-Enabled Voting on EVM Platforms. -- AutoLabel: Automated Textual Data Annotation Method based on Active Learning and Large Language Model. -- KDTSS: A Blockchain-based Scheme for Knowledge Data Traceability and Secure Sharing. -- A Joint Client-Server Watermarking Framework for Federated Learning. -- Robust Representation Learning for Image Clustering.
• Sommario/riassunto: The five-volume set LNCS 14884, 14885, 14886, 14887 & 14888 constitutes the refereed deadline proceedings of the 17th International Conference on Knowledge Science, Engineering and Management, KSEM 2024, held in Birmingham, UK, during August 16–18, 2024. The 160 full papers presented in these proceedings were carefully reviewed and selected from 495 submissions. The papers are organized in the following topical sections: Volume I: Knowledge Science with Learning and AI (KSLA) Volume II: Knowledge Engineering Research and Applications (KERA) Volume III: Knowledge Management with Optimization and Security (KMOS) Volume IV: Emerging Technology Volume V: Special Tracks.
• Titolo autorizzato: Knowledge Science, Engineering and Management
• ISBN: 981-9755-01-8
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910878060703321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Artificial Intelligence, . 2945-9141 ; ; 14887