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

Aus der Reihe Lecture Notes in Computer Science
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68,99 € UVP 79,17 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

26.07.2024

Abbildungen

XIV, 464 p. 124 illus., 109 illus. in color.

Herausgeber

Cungeng Cao + weitere

Verlag

Springer Singapore

Seitenzahl

464

Maße (L/B/H)

23,5/15,5/2,6 cm

Gewicht

721 g

Auflage

2024

Sprache

Englisch

ISBN

978-981-9754-94-6

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

26.07.2024

Abbildungen

XIV, 464 p. 124 illus., 109 illus. in color.

Herausgeber

Verlag

Springer Singapore

Seitenzahl

464

Maße (L/B/H)

23,5/15,5/2,6 cm

Gewicht

721 g

Auflage

2024

Sprache

Englisch

ISBN

978-981-9754-94-6

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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

  • .- 
    Knowledge Engineering Research and Applications (KERA)
    .


    .- Research on Node Cluster Analysis in Brain Connection Data.


    .- A New Emotion Classification Method Based on JAN-VMD.


    .- Neuro-Genetic System: A Hybrid System of CNN-BiLSTM Optimized by Genetic Algorithm for Road Accident Severity Prediction.


    .- MoveFormer: Spatial Graph Periodic Injection Network for Next POI Recommendation.


    .- Bio-Inspired Feature Selection via An Improved Binary Golden Jackal Optimization Algorithm.


    .- Dynamic Reliability-optimised and Energy-efficient Scheduling Algorithms in Heterogeneous Multi-core Systems.


    .- A Human-Computer Negotiation Model Based on Sentiment Analysis and Big Data.


    .- A novel online sequential learning algorithm for ELM based on optimal control.


    .- DICES: Diffusion-Based Contrastive Learning with Knowledge Graphs for Recommendation.


    .- Variational Loss of Random Sampling for Searching Cluster Number.


    .- DVDNER: Dual-view Learning Named Entity Recognition via Diffusion.


    .- Achieving Universal Fairness in Machine Learning: A Multi-objective Optimization Perspective.


    .- SSNF: Optimizing Entity Alignment with a Novel Structural and Semantic Neighbor Filtering.


    .- Visual Analytics of Learning Behavior Based on the Dendritic Neuron Model.


    .- Feature Matching Based Heterogeneous Transfer Learn-ing for Student Performance Prediction.


    .- Weighted Multiple Source-Free Domain Adaptation Ensemble Network in Intelligent Machinery Fault Diagnosis.


    .- Logarithm of Maximum Posterior Evidence: Advanced Model Selection for Text Classification.


    .- A Hybrid Method Combing Reinforcement Learning and Heuristics in Solving Two-Echelon Vehicle Routing Problem with Backhauls.


    .- AgriBERT: A Joint Entity Relation Extraction Model Based on Agricultural Text.


    .- Research on Key Node Cluster Identification Algorithm based on Louvain and Cycle Ratio.


    .- Uncertain $k$ center Clustering, Revisited: Point Assignment.


    .- DPSPC: A Density Peak-based Statistical Parallel Clustering Algorithm for Big Data.


    .- Insert Commonsense Knowledge through Semantics for Dialogue Generation.


    .- Entity Set Expansion based on Category Prompts in MOOCs.


    .- ViT Hybrid Channel Fit Pruning Algorithm for Co-Optimization of Hardware and Software for Edge Device.


    .- Collaborative Adversarial Learning for Unsupervised Federated Domain Adaptation.


    .- Improving Image Captioning with Image Concepts of Words.


    .- M HGN: Multi information Enhanced Heterogeneous Graph Network for Multi-party Dialogue Reading Comprehension.


    .- A Student Performance Prediction Model Based on Feature Factor Transfer.


    .- A Binary Multi-objective Grey Wolf Optimization for Feature Selection.


    .- CS Net: A Coarse-to-fine-grained Summarization Network for Community-based Question Answering Summarization.


    .- AutoIE: An Automated Framework for Information Extraction from Scientific Literature.


    .- Adaptive Density Peak Clustering with Optimized Border-peeling.


    .- Efficient Affinity Propagation Clustering Based on Szemer´edi’s Regularity Lemma.