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…mehr
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)
.- 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.
.- 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.
