Knowledge Science, Engineering and Management (eBook, PDF)

15th International Conference, KSEM 2022, Singapore, August 6-8, 2022, Proceedings, Part II
Redaktion: Memmi, Gerard; Qiu, Meikang; Zhang, Tianwei; Kong, Linghe; Yang, Baijian

• Format: PDF

Produktbeschreibung

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)

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 701
• Erscheinungstermin: 19. Juli 2022
• Englisch
• ISBN-13: 9783031109867
• Artikelnr.: 64377848

Inhaltsangabe

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 KeyphraseGeneration 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.