| WFIM: weighted frequent itemset mining with a weight range and a minimum weight U Yun, JJ Leggett Proceedings of the 2005 SIAM international conference on data mining, 636-640, 2005 | 196 | 2005 |
| High utility itemset mining with techniques for reducing overestimated utilities and pruning candidates U Yun, H Ryang, KH Ryu Expert Systems with Applications 41 (8), 3861-3878, 2014 | 171 | 2014 |
| ASRNN: A recurrent neural network with an attention model for sequence labeling JCW Lin, Y Shao, Y Djenouri, U Yun Knowledge-Based Systems 212, 106548, 2021 | 168 | 2021 |
| Sliding window based weighted maximal frequent pattern mining over data streams G Lee, U Yun, KH Ryu Expert Systems with Applications 41 (2), 694-708, 2014 | 129 | 2014 |
| Top-k high utility pattern mining with effective threshold raising strategies H Ryang, U Yun Knowledge-Based Systems 76, 109-126, 2015 | 121 | 2015 |
| Efficient mining of weighted interesting patterns with a strong weight and/or support affinity U Yun Information Sciences 177 (17), 3477-3499, 2007 | 120 | 2007 |
| Efficient frequent pattern mining based on linear prefix tree G Pyun, U Yun, KH Ryu Knowledge-Based Systems 55, 125-139, 2014 | 112 | 2014 |
| Damped window based high average utility pattern mining over data streams U Yun, D Kim, E Yoon, H Fujita Knowledge-Based Systems 144, 188-205, 2018 | 108 | 2018 |
| WSpan: Weighted Sequential pattern mining in large sequence databases U Yun, JJ Leggett 2006 3Rd international IEEE conference intelligent systems, 512-517, 2006 | 103 | 2006 |
| High utility pattern mining over data streams with sliding window technique H Ryang, U Yun Expert Systems with Applications 57, 214-231, 2016 | 99 | 2016 |
| A new framework for detecting weighted sequential patterns in large sequence databases U Yun Knowledge-Based Systems 21 (2), 110-122, 2008 | 99 | 2008 |
| Incremental high utility pattern mining with static and dynamic databases U Yun, H Ryang Applied intelligence 42, 323-352, 2015 | 89 | 2015 |
| Mining maximal frequent patterns by considering weight conditions over data streams U Yun, G Lee, KH Ryu Knowledge-Based Systems 55, 49-65, 2014 | 87 | 2014 |
| An efficient algorithm for mining high utility patterns from incremental databases with one database scan U Yun, H Ryang, G Lee, H Fujita Knowledge-Based Systems 124, 188-206, 2017 | 82 | 2017 |
| A fast perturbation algorithm using tree structure for privacy preserving utility mining U Yun, J Kim Expert Systems with Applications 42 (3), 1149-1165, 2015 | 77 | 2015 |
| Incremental mining of weighted maximal frequent itemsets from dynamic databases U Yun, G Lee Expert Systems with Applications 54, 304-327, 2016 | 76 | 2016 |
| A new efficient approach for mining uncertain frequent patterns using minimum data structure without false positives G Lee, U Yun Future Generation Computer Systems 68, 89-110, 2017 | 73 | 2017 |
| Mining of high average-utility itemsets using novel list structure and pruning strategy U Yun, D Kim Future Generation Computer Systems 68, 346-360, 2017 | 68 | 2017 |
| Mining lossless closed frequent patterns with weight constraints U Yun Knowledge-Based Systems 20 (1), 86-97, 2007 | 68 | 2007 |
| Mining top-k frequent patterns with combination reducing techniques G Pyun, U Yun Applied intelligence 41, 76-98, 2014 | 63 | 2014 |
