Knowledge Science, Engineering and Management

Knowledge Science, Engineering and Management

15th International Conference, KSEM 2022, Singapore, August 6-8, 2022, Proceedings, Part I

Yang, Baijian; Qiu, Meikang; Kong, Linghe; Memmi, Gerard; Zhang, Tianwei

Springer International Publishing AG

07/2022

753

Mole

Inglês

9783031109829

15 a 20 dias

1181

Descrição não disponível.
?Knowledge Science with Learning and AI (KSLA).- A decoupled YOLOv5 with deformable convolution and multi-scale attention.- OTE: An Optimized Chinese Short Text Matching Algorithm based on External Knowledge.- KIR: A Knowledge--enhanced Interpretable Recommendation Method.- ICKEM: a tool for estimating one's understanding of conceptual knowledge.- Cross-perspective Graph Contrastive Learning.- A Multi-scale Convolution and Gated Recurrent Unit Based Network for Limit Order Book Prediction.- Pre-train Unified Knowledge Graph Embedding with Ontology.- Improving Dialogue Generation with Commonsense Knowledge Fusion and Selection.- A Study of Event Multi-triple Extraction Methods Based on Edge-Enhanced Graph Convolution Networks.- Construction Research and Applications of Industry Chain Knowledge Graphs.- Query and Neighbor-aware Reasoning based Multi-hop Question Answering over Knowledge Graph.- Question Answering over Knowledge Graphs with Query Path Generation.- Improving ParkingOccupancy Prediction in Poor Data Conditions through Customization and Learning to Learn.- Knowledge Concept Recommender Based on Structure Enhanced Interaction Graph Neural Network.- Answering Complex Questions on Knowledge Graphs.- Multi-Attention User Information Based Graph Convolutional Networks for Explainable Recommendation.- Edge-shared GraphSAGE: A New Method of Buffer Calculation for Parallel Management of Big Data Project Schedule.
artificial intelligence;computational linguistics;computer networks;computer systems;data mining;databases;directed graphs;graphic methods;image processing;information retrieval;knowledge-based system;machine learning;natural language processing;network protocols;neural networks;NLP;signal processing;theoretical computer science;weighted graph