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 1618, 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.

Inhalt
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 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.