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Knowledge Science, Engineering and Management 17th International Conference, KSEM 2024, Birmingham, UK, August 16–18, 2024, Proceedings, Part I

Aus der Reihe Lecture Notes in Computer Science
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69,99 € UVP 79,17 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

26.07.2024

Herausgeber

Cungeng Cao + weitere

Verlag

Springer Singapore

Seitenzahl

449

Maße (L/B/H)

23,5/15,5/2,5 cm

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-981-9754-91-5

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

26.07.2024

Herausgeber

Verlag

Springer Singapore

Seitenzahl

449

Maße (L/B/H)

23,5/15,5/2,5 cm

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-981-9754-91-5

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Knowledge Science, Engineering and Management
  • Produktbild: Knowledge Science, Engineering and Management

  • .- 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.