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Knowledge science, engineering and m...
KSEM (Conference) (2021 :)

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  • Knowledge science, engineering and management = 15th International Conference, KSEM 2022, Singapore, August 6-8, 2022 : proceedings.. Part II /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Knowledge science, engineering and management/ edited by Gerard Memmi ... [et al.].
    其他題名: 15th International Conference, KSEM 2022, Singapore, August 6-8, 2022 : proceedings.
    其他題名: KSEM 2022
    其他作者: Memmi, Gerard.
    團體作者: KSEM (Conference)
    出版者: Cham :Springer International Publishing : : 2022.,
    面頁冊數: xv, 701 p. :ill. (chiefly color), digital ;24 cm.
    內容註: 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.
    Contained By: Springer Nature eBook
    標題: Knowledge acquisition (Expert systems) - Congresses. -
    電子資源: https://doi.org/10.1007/978-3-031-10986-7
    ISBN: 9783031109867
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W9444039 電子資源 11.線上閱覽_V 電子書 EB QA76.76.E95 K74 2021 一般使用(Normal) 在架 0
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