The three-volume sets constitute the refereed proceedings of the 15th International Conference on Knowledge Science, Engineering and Management, KSEM 2022, held in Singapore, during August 6-8, 2022.
The 169 full papers presented in these proceedings were carefully reviewed and selected from 498 submissions. The papers are organized in the following topical sections:
Volume I: Knowledge Science with Learning and AI (KSLA)
Volume II: Knowledge Engineering Research and Applications (KERA)
Volume III: Knowledge Management with Optimization and Security (KMOS)
Reihe
Auflage
Sprache
Verlagsort
Verlagsgruppe
Springer International Publishing
Illustrationen
168
88 s/w Abbildungen, 168 farbige Abbildungen
XXVIII, 753 p. 256 illus., 168 illus. in color.
ISBN-13
978-3-031-10983-6 (9783031109836)
DOI
10.1007/978-3-031-10983-6
Schweitzer Klassifikation
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.
