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Lee, Junghye (이정혜)

Department: Department of Industrial Engineering(산업공학과)

Website: http://dm.unist.ac.kr/

Lab: Data Mining Lab. (데이터마이닝 연구실)

Research Keywords: 데이터마이닝, 기계학습, 텍스트마이닝, 연합 학습, 분산 학습, Data Mining, Machine Learning, Text mining

Research Interests: We are pursuing to develop the best algorithms, systems, and applications especially for predictive analysis and data privacy and security, which help solving important industrial and management problems and creating value.

This table browses all dspace content
Issue Date	Title	Author(s)	Type	View	Altmetrics
2021-11	A Multi-stage Data Mining Approach for Liquid Bulk Cargo Volume Analysis based on Bill of Lading Data	Kim, Suhyeon; Sohn, Wonho; Lim, Dongcheol, et al	ARTICLE	76	A Multi-stage Data Mining Approach for Liquid Bulk Cargo Volume Analysis based on Bill of Lading Data
2021-08	Bilingual Autoencoder-based Efficient Harmonization of Multi-source Private Data for Accurate Predictive Modeling	Lee, Taek-Ho; Lee, Junghye; Jun, Chi-Hyuck	ARTICLE	68	Bilingual Autoencoder-based Efficient Harmonization of Multi-source Private Data for Accurate Predictive Modeling
2021-03	An efficient multivariate feature ranking method for gene selection in high-dimensional microarray data	Lee, Junghye; Choi, Inyoung; Jun, Chi-Hyuck	ARTICLE	291	An efficient multivariate feature ranking method for gene selection in high-dimensional microarray data
2020-11	Markov blanket-based universal feature selection for classification and regression of mixed-type data	Lee, Junghye; Jeong, Jun-Yong; Jun, Chi-Hyuck	ARTICLE	437	Markov blanket-based universal feature selection for classification and regression of mixed-type data
2020-08	Word2vec-based latent semantic analysis (W2V-LSA) for topic modeling: A study on blockchain technology trend analysis	Kim, Suhyeon; Park, Haecheong; Lee, Junghye	ARTICLE	331	Word2vec-based latent semantic analysis (W2V-LSA) for topic modeling: A study on blockchain technology trend analysis
2020-04	Different Spectral Domain Transformation for Land Cover Classification Using Convolutional Neural Networks with Multi-Temporal Satellite Imagery	Lee, Junghee; Han, Daehyeon; Shin, Minso, et al	ARTICLE	212	Different Spectral Domain Transformation for Land Cover Classification Using Convolutional Neural Networks with Multi-Temporal Satellite Imagery
2020-01	Secure and Differentially Private Logistic Regression for Horizontally Distributed Data	Kim, Miran; Lee, Junghye; Ohno-Machado, Lucila, et al	ARTICLE	581	Secure and Differentially Private Logistic Regression for Horizontally Distributed Data
2018-12	Convolutional Neural Network-Based Land Cover Classification Using 2-D Spectral Reflectance Curve Graphs With Multitemporal Satellite Imagery	Kim, Miae; Lee, Junghee; Han, Daehyun, et al	ARTICLE	492	Convolutional Neural Network-Based Land Cover Classification Using 2-D Spectral Reflectance Curve Graphs With Multitemporal Satellite Imagery
2018-08	A Data-Driven Procedure of Providing a Health Promotion Program for Hypertension Prevention	Lee, Junghye; Kwon, Ryeok-Hwan; Kim, Hyung Woo, et al	ARTICLE	786	A Data-Driven Procedure of Providing a Health Promotion Program for Hypertension Prevention
2018-05	Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources	Huang, Yingxiang; Lee, Junghye; Wang, Shang, et al	ARTICLE	560	Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources
2018-04	Privacy-Preserving Patient Similarity Learning in a Federated Environment: Development and Analysis	Lee, Junghye; Sun, Jimeng; Wang, Fei, et al	ARTICLE	673	Privacy-Preserving Patient Similarity Learning in a Federated Environment: Development and Analysis
2018-04	Deep learning-based monitoring of overshooting cloud tops from geostationary satellite data	Kim, Miae; Lee, Junghye; Im, Jungho	ARTICLE	678	Deep learning-based monitoring of overshooting cloud tops from geostationary satellite data
2018-02	Interleaved incremental association Markov blanket as a potential feature selection method for improving accuracy in near-infrared spectroscopic analysis	Chang, Kyeol; Lee, Junghye; Jun, Chi-Hyuck, et al	ARTICLE	544	Interleaved incremental association Markov blanket as a potential feature selection method for improving accuracy in near-infrared spectroscopic analysis
2016-10	Risk assessment for hypertension and hypertension complications incidences using a Bayesian network	Lee, Junghye; Lee, Wonji; Park, Il-Su, et al	ARTICLE	502	Risk assessment for hypertension and hypertension complications incidences using a Bayesian network
2016	Acquisition of a series of temperature-varied sample spectra to induce characteristic structural changes of components and selection of target-descriptive variables among them for multivariate analysis to improve accuracy	Chang, Kyeol; Lee, Junghye; Jun, Chi-Hyuck, et al	ARTICLE	464	Acquisition of a series of temperature-varied sample spectra to induce characteristic structural changes of components and selection of target-descriptive variables among them for multivariate analysis to improve accuracy
2015-10	Kernel-based calibration methods combined with multivariate feature selection to improve accuracy of near-infrared spectroscopic analysis	Lee, Junghye; Chang, Kyeol; Jun, Chi-Hyuck, et al	ARTICLE	527	Kernel-based calibration methods combined with multivariate feature selection to improve accuracy of near-infrared spectroscopic analysis
2015-06	Classification of High Dimensionality Data through Feature Selection Using Markov Blanket	Lee, Junghye; Jun, Chi-Hyuck	ARTICLE	481	Classification of High Dimensionality Data through Feature Selection Using Markov Blanket
2015-03	Causality Analysis for Public and Private Expenditures on Health Using Panel Granger-Causality Test	Lee, Su-Dong; Lee, Junghye; Jun, Chi-Hyuck	ARTICLE	529	Causality Analysis for Public and Private Expenditures on Health Using Panel Granger-Causality Test
2014-12	Prediction of Hypertension Complications Risk Using Classification Techniques	Lee, Wonji; Lee, Junghye; Lee, Hyeseon, et al	ARTICLE	501	Prediction of Hypertension Complications Risk Using Classification Techniques

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