Knowledge Science, Engineering and Management
16th International Conference, KSEM 2023, Guangzhou, China, August 16-18, 2023, Proceedings, Part IV
(Sprache: Englisch)
This volume set constitutes the refereed proceedings of the 16th International Conference on Knowledge Science, Engineering and Management, KSEM 2023, which was held in Guangzhou, China, during August 16-18, 2023.
The 114 full papers and 30 short...
The 114 full papers and 30 short...
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Klappentext zu „Knowledge Science, Engineering and Management “
This volume set constitutes the refereed proceedings of the 16th International Conference on Knowledge Science, Engineering and Management, KSEM 2023, which was held in Guangzhou, China, during August 16-18, 2023. The 114 full papers and 30 short papers included in this book were carefully reviewed and selected from 395 submissions. They were organized in topical sections as follows: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management systems; and emerging technologies for knowledge science, engineering and management.
Inhaltsverzeichnis zu „Knowledge Science, Engineering and Management “
Emerging technologies for Knowledge science, engineering and management.- Federated Prompting and Chain-of-Thought Reasoning for Improving LLMs Answering.- Advancing Domain Adaptation of BERT by Learning Domain Term Semantics.- Deep Reinforcement Learning for Group-Aware Robot Navigation in Crowds.- An Enhanced Distributed Algorithm for Area Skyline Computation based on Apache Spark.- TCMCoRep: Traditional Chinese Medicine data mining with Contrastive Graph Representation Learning.- Local-Global Fusion Augmented Graph Contrastive Learning Based on Generative Models.- PRACM: Predictive Rewards for Actor-Critic with Mixing Function in Multi-Agent Reinforcement Learning.- A Cybersecurity Knowledge Graph Completion Method for Scalable Scenarios.- Research on remote sensing image classification based on Transfer learning and Data Augmentation.- Multivariate Long-Term Traffic Forecasting with Graph Convolutional Network and Historical Attention Mechanism.- Multi-hop Reading Comprehension Learning Method Based on Answer Contrastive Learning.- Importance-based Neuron Selective Distillation for Interference Mitigation in Multilingual Neural Machine Translation.- Are GPT Embeddings Useful for Ads and Recommendation?.- Modal interaction-enhanced Prompt Learning by transformer decoder for Vision-Language Models.- Unveiling Cybersecurity Threats from Online Chat Groups: A Triple Extraction Approach.- KSRL: Knowledge Selection based Reinforcement Learning for Knowledge-Grounded Dialogue.- Prototype-Augmented Contrastive Learning for Few-shot Unsupervised Domain Adaptation.- Style Augmentation and Domain-aware Parametric Contrastive Learning for Domain Generalization.- Recent Progress on Text Summarisation Based on BERT and GPT.- Ensemble Strategy Based on Deep Reinforcement Learning for Portfolio Optimization.- A Legal Multi-Choice Question Answering Model Based on BERT
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and Attention.- Offline Reinforcement Learning with Diffusion-Based Behavior Cloning Term.- Evolutionary Verbalizer Search for Prompt-based Few Shot Text Classification.- Graph Contrastive Learning Method with Sample Disparity Constraint and Feature Structure Graph for Node Classification.- Learning Category Discriminability for Active Domain Adaptation.- Multi-Level Contrastive Learning for Commonsense Question Answering.- Efficient Hash Coding for Image Retrieval based on Improved Center Generation and Contrastive Pre-training Knowledge Model.- Univarite Time Series Forecasting via Interactive Learning.- Task Inference for Offline Meta Reinforcement Learning via Latent Shared Knowledge.- A Quantitative Spectra Analysis Framework Combining Mixup and Band Attention for Predicting Soluble Solid Content of Blueberries.- Contextualized Hybrid Prompt-Tuning for Generation-Based Event Extraction.- udPINNs: An Enhanced PDE Solving Algorithm Incorporating Domain of Dependence Knowledge.- Joint Community and Structural Hole Spanner Detection via Graph Contrastive Learning.- A Reinforcement Learning-based Approach for Continuous Knowledge Graph Construction.- A Multifactorial Evolutionary Algorithm based on Model Knowledge Transfer.- Knowledge Leadership, AI Technology Adoption and Big Data Application Ability.- RFLSem: A lightweight model for textual sentiment analysis.
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Bibliographische Angaben
- 2023, 1st ed. 2023, XXIV, 471 Seiten, 112 farbige Abbildungen, Masse: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben: Zhi Jin, Yuncheng Jiang, Robert Andrei Buchmann, Yaxin Bi, Ana-Maria Ghiran, Wenjun Ma
- Verlag: Springer, Berlin
- ISBN-10: 303140291X
- ISBN-13: 9783031402913
Sprache:
Englisch
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