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5篇 您的检索式：作者名="SunHee Kim"

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		题名	作者	年代	出处	被引量
	1	Antidepressant effect of Chaihu-Shugan-San extract and its constituents in rat models of depression显示文摘	Jin Han DaeHyun Seog	2005	Life Sciences2005，76，11：	1
	2	Transgene structures in T-DNA-inserted rice plants显示文摘	Sung-Ryul Kim Jinwon Lee Sung-Hoon Jun Sunhee Park Hong-Gyu Kang Soontae Kwon Gynheung An	2003	Plant Molecular Biology2003，，4：	1
	3	How are consumers, service and market factors related to customer loyalty in medical service显示文摘	Sunhee Lee Hyunmi Kim Juhye Kim Gwiyeom Ha	2008	J Prey Med Public Health2008，41，5：	1
	4	岛轩怡然——韩国Island住宅显示文摘这个依山面江而建被唤作Island House的大房子,每一间都有如画的风景取悦你的全身心和视线。它建在韩国江原道的汉江河域,面积达约700m^2,像一只巨大的玻璃钢架船,以不凡的姿态伫立在在波光粼粼的汉江之畔。	SuMi Jung JungMin Oh ARum Kim SunHee Kim JongOh Ki	2011	中国建筑装饰装修2011，，5：	0
	5	Clustering-based label estimation for network anomaly detection显示文摘A substantial body of work has been done to identify network anomalies using supervised and unsupervised learning techniques with their unique strengths and weaknesses.In this work,we propose a new approach that takes advantage of both worlds of unsupervised and supervised learnings.The main objective of the proposed approach is to enable supervised anomaly detection without the provision of the associated labels by users.To this end,we estimate the labels of each connection in the training phase using clustering.The“estimated”labels are then utilized to establish a supervised learning model for the subsequent classification of connections in the testing stage.We set up a new property that defines anomalies in the context of network anomaly detection to improve the quality of estimated labels.Through our extensive experiments with a public dataset(NSL-KDD),we will prove that the proposed method can achieve performance comparable to one with the “original”labels provided in the dataset.We also introduce two heuristic functions that minimize the impact of the randomness of clustering to improve the overall quality of the estimated labels.	Sunhee Baek Donghwoon Kwon Sang C.Suh Hyunjoo Kim Ikkyun Kim Jinoh Kim	2021	Digital Communications and Networks2021，7，1：	0

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