Knowledge Science, Engineering and Management: 15th International Conference, Ksem 2022, Singapore, August 6-8, 2022, Proceedings, Part II

ISBN-13: 9783031109850 / Angielski / Miękka / 2022

Memmi, Gerard

Opis

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)

Spis treści

​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.