Knowledge Science, Engineering and Management

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Details

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 68, 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)


Inhalt
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.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783031109850
    • Genre Information Technology
    • Auflage 1st edition 2022
    • Editor Gerard Memmi, Baijian Yang, Meikang Qiu, Tianwei Zhang, Linghe Kong
    • Lesemotiv Verstehen
    • Anzahl Seiten 720
    • Größe H235mm x B155mm x T39mm
    • Jahr 2022
    • EAN 9783031109850
    • Format Kartonierter Einband
    • ISBN 3031109856
    • Veröffentlichung 31.07.2022
    • Titel Knowledge Science, Engineering and Management
    • Untertitel 15th International Conference, KSEM 2022, Singapore, August 6-8, 2022, Proceedings, Part II
    • Gewicht 1072g
    • Herausgeber Springer International Publishing
    • Sprache Englisch

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