Knowledge Science, Engineering and Management [electronic resource] : 17th International Conference, KSEM 2024, Birmingham, UK, August 16-18, 2024, Proceedings, Part I / edited by Cungeng Cao, Huajun Chen, Liang Zhao, Junaid Arshad, Taufiq Asyhari, Yonghao Wang.

Colaborador(es): Cao, Cungeng [editor.] | Chen, Huajun [editor.] | Zhao, Liang [editor.] | Arshad, Junaid [editor.] | Asyhari, Taufiq [editor.] | Wang, Yonghao [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Lecture Notes in Artificial Intelligence ; 14884Editor: Singapore : Springer Nature Singapore : Imprint: Springer, 2024Edición: 1st ed. 2024Descripción: XIII, 449 p. 136 illus., 124 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9789819754922Tema(s): 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 ApplicationsFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q334-342TA347.A78Recursos en línea: Libro electrónicoTexto
Contenidos:
-- Knowledge Science with Learning and AI (KSLA). -- A Deep Correlation Feature Extraction Network: Intelligent Description of Bearing Fault Knowledge for Zero-Sample Learning. -- Elastic Filter Prune in Deep Neural Networks using Modified Weighted Hybrid Criterion. -- EE LCE: An Event Extraction Framework Based on LLM Generated CoT Explanation. -- Attention and Learning Features enhanced Knowledge Tracing. -- An MLM Decoding Space Enhancement for Legal Document Proofreading. -- Meta Pruning: learning to prune on few shot learning. -- Knowledge informed Molecular Learning: A Survey on Paradigm Transfer. .-GenFlowchart: Parsing and Understanding Flowchart Using Generative AI. -- DSCVSR: A Lightweight Video Super-Resolution for Arbitrary Magnification. -- Programming Knowledge Tracing with Context and Structure Integration. -- An Konwledge-Based Semi-supervised Active Learning Method for Precision Pest Disease Diagnostic. -- Multi-Label Feature Selection with Adaptive Subspace Learning. -- User Story Classification with Machine Learning and LLMs. -- PTMA: Pre-trained Model Adaptation for Transfer Learning. -- Optimization Strategies for Knowledge Graph Based Distractor Generation. -- Reinforced Subject-aware Graph Neural Network for Related Work Generation. -- EFCC IeT: Cross-modal Electronic File Content Correlation via Image-enhanced Text. -- Multi relation Neural Network Recommendation Model Based on Knowledge Graph Embedding Algorithm. -- Link prediction based on deep global information in heterogeneous graph. -- Subject Knowledge Entity Relationship Extraction Based on Multi-Feature Fusion and Relation Specific Horns Tagging. -- A Human Computer Negotiation Model Based on Q-Learning. -- Affine Transformation-Based Knowledge Graph Embedding. -- Integrating Prior Scenario Knowledge for Composition Review Generation. -- Distant supervised relation extraction on pre-train model with improved multi-label attention mechanism. -- sEMG-based Multi-View Feature-Constrained Representation Learning. -- Vicinal Data Augmentation for Classification Model via Feature Weaken. -- STM an Improved Peak Price Tracking-Based Online Portfolio Selection Algorithm. -- Spatiotemporal Dependence Learning with Meteorological Context for Transportation Demand Prediction. -- Automatic Meter Pointer Reading Based on Knowledge Distillation. -- Multi-Table Question Answering Method Based on Correlation Evaluation and Precomputed Cube. -- A Joint Multi-task Learning Model for Web Table-to-Knowledge Graph Matching. -- An In Context Schema Understanding Method for Knowledge Base Question Answering. -- Performance Enhancement Strategies for Node Classification Based on Graph Community Structure Recognition.
En: Springer Nature eBookResumen: 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.
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-- Knowledge Science with Learning and AI (KSLA). -- A Deep Correlation Feature Extraction Network: Intelligent Description of Bearing Fault Knowledge for Zero-Sample Learning. -- Elastic Filter Prune in Deep Neural Networks using Modified Weighted Hybrid Criterion. -- EE LCE: An Event Extraction Framework Based on LLM Generated CoT Explanation. -- Attention and Learning Features enhanced Knowledge Tracing. -- An MLM Decoding Space Enhancement for Legal Document Proofreading. -- Meta Pruning: learning to prune on few shot learning. -- Knowledge informed Molecular Learning: A Survey on Paradigm Transfer. .-GenFlowchart: Parsing and Understanding Flowchart Using Generative AI. -- DSCVSR: A Lightweight Video Super-Resolution for Arbitrary Magnification. -- Programming Knowledge Tracing with Context and Structure Integration. -- An Konwledge-Based Semi-supervised Active Learning Method for Precision Pest Disease Diagnostic. -- Multi-Label Feature Selection with Adaptive Subspace Learning. -- User Story Classification with Machine Learning and LLMs. -- PTMA: Pre-trained Model Adaptation for Transfer Learning. -- Optimization Strategies for Knowledge Graph Based Distractor Generation. -- Reinforced Subject-aware Graph Neural Network for Related Work Generation. -- EFCC IeT: Cross-modal Electronic File Content Correlation via Image-enhanced Text. -- Multi relation Neural Network Recommendation Model Based on Knowledge Graph Embedding Algorithm. -- Link prediction based on deep global information in heterogeneous graph. -- Subject Knowledge Entity Relationship Extraction Based on Multi-Feature Fusion and Relation Specific Horns Tagging. -- A Human Computer Negotiation Model Based on Q-Learning. -- Affine Transformation-Based Knowledge Graph Embedding. -- Integrating Prior Scenario Knowledge for Composition Review Generation. -- Distant supervised relation extraction on pre-train model with improved multi-label attention mechanism. -- sEMG-based Multi-View Feature-Constrained Representation Learning. -- Vicinal Data Augmentation for Classification Model via Feature Weaken. -- STM an Improved Peak Price Tracking-Based Online Portfolio Selection Algorithm. -- Spatiotemporal Dependence Learning with Meteorological Context for Transportation Demand Prediction. -- Automatic Meter Pointer Reading Based on Knowledge Distillation. -- Multi-Table Question Answering Method Based on Correlation Evaluation and Precomputed Cube. -- A Joint Multi-task Learning Model for Web Table-to-Knowledge Graph Matching. -- An In Context Schema Understanding Method for Knowledge Base Question Answering. -- Performance Enhancement Strategies for Node Classification Based on Graph Community Structure Recognition.

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.

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