| Machine learning predictive model based on national data for fatal accidents of construction workers J Choi, B Gu, S Chin, JS Lee Automation in Construction 110, 102974, 2020 | 155 | 2020 |
| Instance categorization by support vector machines to adjust weights in AdaBoost for imbalanced data classification W Lee, CH Jun, JS Lee Information Sciences 381, 92-103, 2017 | 131 | 2017 |
| Classification-based collaborative filtering using market basket data JS Lee, CH Jun, J Lee, S Kim Expert systems with applications 29 (3), 700-704, 2005 | 123 | 2005 |
| Shilling Attack Detection—A New Approach for a Trustworthy Recommender System JS Lee, D Zhu INFORMS Journal on Computing 24 (1), 117-131, 2012 | 111 | 2012 |
| Statistical characterization of the morphologies of nanoparticles through machine learning based electron microscopy image analysis B Lee, S Yoon, JW Lee, Y Kim, J Chang, J Yun, JC Ro, JS Lee, JH Lee ACS nano 14 (12), 17125-17133, 2020 | 100 | 2020 |
| A K-means-like Algorithm for K-medoids Clustering and Its Performance H Park, JS Lee, C Jun Proceedings of the 36th CIE Conference on Computers & Industrial Engineering …, 2006 | 99 | 2006 |
| Two-way cooperative prediction for collaborative filtering recommendations JS Lee, S Olafsson Expert Systems with Applications 36 (3), 5353-5361, 2009 | 75 | 2009 |
| Robust outlier detection using the instability factor J Ha, S Seok, JS Lee Knowledge-Based Systems 63, 15-23, 2014 | 68 | 2014 |
| A new under-sampling method using genetic algorithm for imbalanced data classification J Ha, JS Lee Proceedings of the 10th International Conference on Ubiquitous Information …, 2016 | 67 | 2016 |
| AUC4. 5: AUC-based C4. 5 decision tree algorithm for imbalanced data classification JS Lee IEEE Access 7, 106034-106042, 2019 | 65 | 2019 |
| A precise ranking method for outlier detection J Ha, S Seok, JS Lee Information Sciences 324, 88-107, 2015 | 61 | 2015 |
| Automatic determination of neighborhood size in SMOTE J Yun, J Ha, JS Lee Proceedings of the 10th international conference on ubiquitous information …, 2016 | 51 | 2016 |
| Data mining for recognizing patterns in foodborne disease outbreaks M Thakur, S Olafsson, JS Lee, CR Hurburgh Journal of food engineering 97 (2), 213-227, 2010 | 44 | 2010 |
| A meta-learning approach for determining the number of clusters with consideration of nearest neighbors JS Lee, S Olafsson Information Sciences 232, 208-224, 2013 | 41 | 2013 |
| Data clustering by minimizing disconnectivity JS Lee, S Olafsson Information Sciences 181 (4), 732-746, 2011 | 40 | 2011 |
| Optimizing anode location in impressed current cathodic protection system to minimize underwater electric field using multiple linear regression analysis and artificial neural … YS Kim, S Seok, JS Lee, SK Lee, JG Kim Engineering Analysis with Boundary Elements 96, 84-93, 2018 | 31 | 2018 |
| Incorporating receiver operating characteristics into naive Bayes for unbalanced data classification T Kim, B Do Chung, JS Lee Computing 99 (3), 203-218, 2017 | 29 | 2017 |
| Systematic study of interdependent relationship on gold nanorod synthesis assisted by electron microscopy image analysis S Yoon, B Lee, J Yun, JG Han, JS Lee, JH Lee Nanoscale 9 (21), 7114-7123, 2017 | 26 | 2017 |
| Using data mining techniques to predict win-loss in korean professional baseball games Y Oh, H Kim, J Yun, JS Lee Journal of Korean Institute of Industrial Engineers 40 (1), 8-17, 2014 | 24 | 2014 |
| When costs are unequal and unknown: A subtree grafting approach for unbalanced data classification JS Lee, D Zhu Decision Sciences 42 (4), 803-829, 2011 | 23 | 2011 |
