ETRI-Knowledge Sharing Plaform



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구분 SCI
연도 ~ 키워드


학술대회 A Design of Continuous Learning System based on Knowledge Augmentation
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강현중, 권순현, 김은주, 김현재, 이호성, 김귀훈, 김내수
International Conference on Platform Technology and Service (PlatCon) 2017, pp.1-4
To create an algorithm with Machine Learning, users should understand all the knowledge such as learning rate, activation, dimension reduction, hyper parameter, neural network, etc. Therefore, in order to construct a machine learning procedure, expert knowledge is required. So, it is difficult for general users to use it. Also, experts are also hard to regenerate well-defined model if it is described only in the paper. In this paper, we propose a knowledge based Continuous Learning System (CLS) which persistently collect and infer new knowledge from information for the existing learning setup and results instantiated based on a hierarchically designed ontology model.
KSP 제안 키워드
Continuous learning, Dimension Reduction, Knowledge augmentation, Knowledge-based, Learning System, Learning procedure, Learning rate, Ontology Model, Well-defined, expert knowledge, machine Learning