{"product_id":"9783031402913","title":"Knowledge Science, Engineering and Management : 16th International Conference, KSEM 2023, Guangzhou, China, August 16-18, 2023, Proceedings, Part IV (Lecture Notes in Computer Science 14120) (1st ed. 2023. 2023. xxiv, 471 S. XXIV, 471 p. 124 illus., 112 i","description":"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. \nThe 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.  \u003cb\u003eEmerging technologies for Knowledge science, engineering and management\u003c\/b\u003e.- \u003ci\u003eFederated Prompting and Chain-of-Thought Reasoning for Improving LLMs Answering.- \u003c\/i\u003e\u003ci\u003eAdvancing Domain Adaptation of BERT by Learning Domain Term Semantics.- \u003c\/i\u003e\u003ci\u003eDeep Reinforcement Learning for Group-Aware Robot Navigation in Crowds.- \u003c\/i\u003e\u003ci\u003eAn Enhanced Distributed Algorithm for Area Skyline Computation based on Apache Spark.- \u003c\/i\u003e\u003ci\u003eTCMCoRep: Traditional Chinese Medicine data mining with Contrastive Graph Representation Learning.- \u003c\/i\u003e\u003ci\u003eLocal-Global Fusion Augmented Graph Contrastive Learning Based on Generative Models.- \u003c\/i\u003e\u003ci\u003ePRACM: Predictive Rewards for Actor-Critic with Mixing Function in Multi-Agent Reinforcement Learning.- \u003c\/i\u003e\u003ci\u003eA Cybersecurity Knowledge Graph Completion Method for Scalable Scenarios.- \u003c\/i\u003e\u003ci\u003eResearch on remote sensing image classification based on Transfer learning and Data Augmentation.- \u003c\/i\u003e\u003ci\u003eMultivariate Long-Term Traffic Forecasting with Graph Convolutional Network and Historical Attention Mechanism.- \u003c\/i\u003e\u003ci\u003eMulti-hop Reading Comprehension Learning Method Based on Answer Contrastive Learning.- \u003c\/i\u003e\u003ci\u003eImportance-based Neuron Selective Distillation for Interference Mitigation in Multilingual Neural Machine Translation.- \u003c\/i\u003e\u003ci\u003eAre GPT Embeddings Useful for Ads and Recommendation?.- \u003c\/i\u003e\u003ci\u003eModal interaction-enhanced Prompt Learning by transformer decoder for Vision-Language Models.- \u003c\/i\u003e\u003ci\u003eUnveiling Cybersecurity Threats from Online Chat Groups: A Triple Extraction Approach.- \u003c\/i\u003e\u003ci\u003eKSRL: Knowledge Selection based Reinforcement Learning for Knowledge-Grounded Dialogue.- \u003c\/i\u003e\u003ci\u003ePrototype-Augmented Contrastive Learning for Few-shot Unsupervised Domain Adaptation.- \u003c\/i\u003e\u003ci\u003eStyle Augmentation and Domain-aware Parametric Contrastive Learning for Domain Generalization.- \u003c\/i\u003e\u003ci\u003eRecent Progress on Text Summarisation Based on BERT and GPT.- \u003c\/i\u003e\u003ci\u003eEnsemble Strategy Based on Deep Reinforcement Learning for Portfolio Optimization.- \u003c\/i\u003e\u003ci\u003eA Legal Multi-Choice Question Answering Model Based on BERT and Attention.- \u003c\/i\u003e\u003ci\u003eOffline Reinforcement Learning with Diffusion-Based Behavior Cloning Term.- \u003c\/i\u003e\u003ci\u003eEvolutionary Verbalizer Search for Prompt-based Few Shot Text Classification.- \u003c\/i\u003e\u003ci\u003eGraph Contrastive Learning Method with Sample Disparity Constraint and Feature Structure Graph for Node Classification.- \u003c\/i\u003e\u003ci\u003eLearning Category Discriminability for Active Domain Adaptation.- \u003c\/i\u003e\u003ci\u003eMulti-Level Contrastive Learning for Commonsense Question Answering.- \u003c\/i\u003e\u003ci\u003eEfficient Hash Coding for Image Retrieval based on Improved Center Generation and Contrastive Pre-training Knowledge Model.- \u003c\/i\u003e\u003ci\u003eUnivarite Time Series Forecasting via Interactive Learning.- \u003c\/i\u003e\u003ci\u003eTask Inference for Offline Meta Reinforcement Learning via Latent Shared Knowledge.- \u003c\/i\u003e\u003ci\u003eA Quantitative Spectra Analysis Framework Combining Mixup and Band Attention for Predicting Soluble Solid Content of Blueberries.- \u003c\/i\u003e\u003ci\u003eContextualized Hybrid Prompt-Tuning for Generation-Based Event Extraction.- \u003c\/i\u003e\u003ci\u003eudPINNs: An Enhanced PDE Solving Algorithm Incorporating Domain of Dependence Knowledge.- \u003c\/i\u003e\u003ci\u003eJoint Community and Structural Hole Spanner Detection via Graph Contrastive Learning.- \u003c\/i\u003e\u003ci\u003eA Reinforcement Learning-based Approach for Continuous Knowledge Graph Construction.- \u003c\/i\u003e\u003ci\u003eA Multifactorial Evolutionary Algorithm based on Model Knowledge Transfer.- \u003c\/i\u003e\u003ci\u003eKnowledge Leadership, AI Technology Adoption and Big Data Application Ability.- \u003c\/i\u003e\u003ci\u003eRFLSem: A lightweight model for textual sentiment analysis.\u003c\/i\u003e","brand":"SPRINGER, BERLIN; SPRINGER NATURE SWITZERLAND; SPRING","offers":[{"title":"Default Title","offer_id":49839793340664,"sku":"00000_00000_00000_00000","price":176.23,"currency_code":"AUD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/8208\/6904\/files\/9783031402913-1.jpg?v=1783772439","url":"https:\/\/kinokuniya.com.au\/products\/9783031402913","provider":"Books Kinokuniya Australia","version":"1.0","type":"link"}