UID:
almahu_9949335243602882
Umfang:
XV, 701 p. 226 illus., 195 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2022.
ISBN:
9783031109867
Serie:
Lecture Notes in Artificial Intelligence ; 13369
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 Engineering Research and Applications (KERA) -- Multi-View Heterogeneous Network Embedding -- A Multi-level Attention-based LSTM Network for Ultra-short-term Solar Power Forecast using Meteorological Knowledge -- Unsupervised Person Re-ID via Loose-Tight Alternate Clustering -- Sparse Dense Transformer Network for Video Action Recognition -- Deep User Multi-Interest Network for Click-Through Rate Prediction -- Open Relation Extraction via Query-based Span Prediction -- Relational Triple Extraction with Relation-Attentive Contextual Semantic Representations -- Mario Fast Learner: Fast and Efficient solutions for Super Mario Bros -- Few-shot Learning with Self-supervised Classifier for Complex Knowledge Base Question Answering -- Data-driven Approach for Investigation of Irradiation Hardening Behavior of RAFM Steel -- Deep-to-bottom Weights Decay: A Systemic Knowledge Review Learning Technique for Transformer Layers in Knowledge Distillation -- Topic and Reference Guided Keyphrase Generation from Social Media -- DISEL: A Language for Specifying DIS-based Ontologies -- MSSA-FL:High-Performance Multi-Stage Semi-Asynchronous Federated Learning with Non-IID Data -- A GAT-based Chinese Text Classification Model: Using of Redical Guidance and Association Between Characters Across Sentences -- Incorporating Explanation to Balance the Exploration and Exploitation of Deep Reinforcement Learning.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783031109850
Weitere Ausg.:
Printed edition: ISBN 9783031109874
Sprache:
Englisch
DOI:
10.1007/978-3-031-10986-7
URL:
https://doi.org/10.1007/978-3-031-10986-7
