| Location-based recommendation system using bayesian user’s preference model in mobile devices MH Park, JH Hong, SB Cho International conference on ubiquitous intelligence and computing, 1130-1139, 2007 | 514 | 2007 |
| Understanding and prediction of mobile application usage for smart phones C Shin, JH Hong, AK Dey proceedings of the 2012 ACM conference on ubiquitous computing, 173-182, 2012 | 328 | 2012 |
| Factors influencing quality of experience of commonly used mobile applications S Ickin, K Wac, M Fiedler, L Janowski, JH Hong, AK Dey IEEE Communications Magazine 50 (4), 48-56, 2012 | 293 | 2012 |
| Getting closer: an empirical investigation of the proximity of user to their smart phones AK Dey, K Wac, D Ferreira, K Tassini, JH Hong, J Ramos Proceedings of the 13th international conference on Ubiquitous computing …, 2011 | 247 | 2011 |
| A smartphone-based sensing platform to model aggressive driving behaviors JH Hong, B Margines, AK Dey Proceedings of the SIGCHI Conference on Human Factors in Computing Systems …, 2014 | 183 | 2014 |
| Fingerprint classification using one-vs-all support vector machines dynamically ordered with naı¨ ve Bayes classifiers JH Hong, JK Min, UK Cho, SB Cho Pattern Recognition 41 (2), 662-671, 2008 | 166 | 2008 |
| The classification of cancer based on DNA microarray data that uses diverse ensemble genetic programming JH Hong, SB Cho Artificial intelligence in Medicine 36 (1), 43-58, 2006 | 112 | 2006 |
| Efficient huge-scale feature selection with speciated genetic algorithm JH Hong, SB Cho Pattern Recognition Letters 27 (2), 143-150, 2006 | 109 | 2006 |
| Toward personalized activity recognition systems with a semipopulation approach JH Hong, J Ramos, AK Dey IEEE Transactions on Human-Machine Systems 46 (1), 101-112, 2015 | 79 | 2015 |
| Understanding physiological responses to stressors during physical activity JH Hong, J Ramos, AK Dey Proceedings of the 2012 ACM conference on ubiquitous computing, 270-279, 2012 | 70 | 2012 |
| A probabilistic multi-class strategy of one-vs.-rest support vector machines for cancer classification JH Hong, SB Cho Neurocomputing 71 (16-18), 3275-3281, 2008 | 65 | 2008 |
| A semantic Bayesian network approach to retrieving information with intelligent conversational agents KM Kim, JH Hong, SB Cho Information Processing & Management 43 (1), 225-236, 2007 | 63 | 2007 |
| Studying the experience of mobile applications used in different contexts of daily life K Wac, S Ickin, JH Hong, L Janowski, M Fiedler, AK Dey Proceedings of the first ACM SIGCOMM workshop on Measurements up the stack, 7-12, 2011 | 58 | 2011 |
| ConaMSN: A context-aware messenger using dynamic Bayesian networks with wearable sensors JH Hong, SI Yang, SB Cho Expert Systems with Applications 37 (6), 4680-4686, 2010 | 49 | 2010 |
| A novel evolutionary approach to image enhancement filter design: method and applications JH Hong, SB Cho, UK Cho IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 39 …, 2009 | 48 | 2009 |
| Evolution of emergent behaviors for shooting game characters in robocode JH Hong, SB Cho Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No …, 2004 | 47 | 2004 |
| Competitive live evaluations of activity-recognition systems H Gjoreski, S Kozina, M Gams, M Lustrek, JA Álvarez-García, JH Hong, ... IEEE Pervasive Computing 14 (1), 70-77, 2015 | 44 | 2015 |
| Lymphoma cancer classification using genetic programming with SNR features JH Hong, SB Cho European Conference on Genetic Programming, 78-88, 2004 | 40 | 2004 |
| Route guidance modality for elder driver navigation SJ Kim, JH Hong, KA Li, J Forlizzi, AK Dey International Conference on Pervasive Computing, 179-196, 2012 | 39 | 2012 |
| Gene boosting for cancer classification based on gene expression profiles JH Hong, SB Cho Pattern Recognition 42 (9), 1761-1767, 2009 | 32 | 2009 |
Sung-Bae ChoYonsei UniversityVerified email at yonsei.ac.kr
