UID:
almahu_9949335243502882
Umfang:
XVI, 753 p. 282 illus., 240 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2022.
ISBN:
9783031109898
Serie:
Lecture Notes in Artificial Intelligence ; 13370
Inhalt:
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).
Anmerkung:
Knowledge Management with Optimization and Security (KMOS) -- Study on Chinese Named Entity Recognition Based on Dynamic Fusion and Adversarial Training -- Spatial Semantic Learning for Travel Time Estimation -- A Fine-Grained Approach for Vulnerabilities Discovery using Augmented Vulnerability Signatures -- PPBR-FL: a Privacy-preserving and Byzantine-robust Federated Learning System -- GAN-Based Fusion Adversarial Training -- MAST-NER: A Low-Resource Named Entity Recognition Method based on Trigger Pool -- Fuzzy information measures feature selection using descriptive statistics data -- Prompt-Based Self-Training Framework for Few-Shot Named Entity Recognition -- Learning Advisor-Advisee Relationship from Multiplex Network Structure -- CorefDRE: Coref-aware Document-level Relation Extraction -- Single Pollutant Prediction Approach by Fusing MLSTM and CNN -- A Multi-objective Evolutionary Algorithm Based on Multi-layer Network Reduction for Community Detection -- Detection DDoS of attacks based on federated learning with Digital Twin Network -- A Privacy-Preserving Subgraph-Level Federated Graph Neural Network via Differential Privacy.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783031109881
Weitere Ausg.:
Printed edition: ISBN 9783031109904
Sprache:
Englisch
DOI:
10.1007/978-3-031-10989-8
URL:
https://doi.org/10.1007/978-3-031-10989-8
