Knowledge Science, Engineering and Management

Knowledge Science, Engineering and Management

15th International Conference, KSEM 2022, Singapore, August 6-8, 2022, Proceedings, Part II

Qiu, Meikang; Kong, Linghe; Memmi, Gerard; Zhang, Tianwei; Yang, Baijian

Springer International Publishing AG

07/2022

701

Mole

Inglês

9783031109850

15 a 20 dias

1086

Descrição não disponível.
?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.
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artificial intelligence;computational linguistics;computer networks,;computer systems;computer vision;data mining;image analysis;image processing;information retrieval;linguistics;machine learning;natural language processing;natural languages;network protocols;neural networks;nlp;pattern recognition;signal processing