Knowledge Science, Engineering and Management (eBook, PDF)

17th International Conference, KSEM 2024, Birmingham, UK, August 16-18, 2024, Proceedings, Part I
Redaktion: Cao, Cungeng; Wang, Yonghao; Asyhari, Taufiq; Arshad, Junaid; Zhao, Liang; Chen, Huajun

• Format: PDF

Produktbeschreibung

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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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 449
• Erscheinungstermin: 25. Juli 2024
• Englisch
• ISBN-13: 9789819754922
• Artikelnr.: 72242815

Inhaltsangabe

.- 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.