| Predicting students' final performance from participation in on-line discussion forums C Romero, MI López, JM Luna, S Ventura Computers & Education 68, 458-472, 2013 | 791 | 2013 |
| Classification via clustering for predicting final marks based on student participation in forums. MI Lopez, JM Luna, C Romero, S Ventura International Educational Data Mining Society, 2012 | 233 | 2012 |
| Frequent itemset mining: A 25 years review JM Luna, P Fournier‐Viger, S Ventura Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 9 (6 …, 2019 | 228 | 2019 |
| Mining rare association rules from e-learning data C Romero, JR Romero, JM Luna, S Ventura Educational Data Mining 2010, 2010 | 135 | 2010 |
| MDM tool: A data mining framework integrated into Moodle JM Luna, C Castro, C Romero Computer Applications in Engineering Education 25 (1), 90-102, 2017 | 104 | 2017 |
| Pattern mining with evolutionary algorithms S Ventura, JM Luna Springer 16, 134-145, 2016 | 104 | 2016 |
| Association rule mining using genetic programming to provide feedback to instructors from multiple‐choice quiz data C Romero, A Zafra, JM Luna, S Ventura Expert Systems 30 (2), 162-172, 2013 | 94 | 2013 |
| Design and behavior study of a grammar-guided genetic programming algorithm for mining association rules JM Luna, JR Romero, S Ventura Knowledge and Information Systems 32, 53-76, 2012 | 88 | 2012 |
| Apriori versions based on mapreduce for mining frequent patterns on big data JM Luna, F Padillo, M Pechenizkiy, S Ventura IEEE transactions on cybernetics 48 (10), 2851-2865, 2017 | 84 | 2017 |
| An advanced review on text mining in medicine C Luque, JM Luna, M Luque, S Ventura Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 9 (3 …, 2019 | 72 | 2019 |
| An evolutionary algorithm for the discovery of rare class association rules in learning management systems JM Luna, C Romero, JR Romero, S Ventura Applied Intelligence 42, 501-513, 2015 | 69 | 2015 |
| LAIM discretization for multi-label data A Cano, JM Luna, EL Gibaja, S Ventura Information Sciences 330 (10), 370–384, 2016 | 66 | 2016 |
| Supervised descriptive pattern mining S Ventura, JM Luna Springer International Publishing, 2018 | 62 | 2018 |
| On the use of genetic programming for mining comprehensible rules in subgroup discovery JM Luna, JR Romero, C Romero, S Ventura IEEE transactions on cybernetics 44 (12), 2329-2341, 2014 | 61 | 2014 |
| Mining association rules on big data through mapreduce genetic programming F Padillo, JM Luna, F Herrera, S Ventura Integrated Computer-Aided Engineering 25 (1), 31-48, 2017 | 58 | 2017 |
| High performance evaluation of evolutionary-mined association rules on GPUs A Cano, JM Luna, S Ventura The Journal of Supercomputing 66, 1438-1461, 2013 | 57 | 2013 |
| Reducing gaps in quantitative association rules: A genetic programming free-parameter algorithm JM Luna, JR Romero, C Romero, S Ventura Integrated Computer-Aided Engineering 21 (4), 321-337, 2014 | 51 | 2014 |
| Speeding-up association rule mining with inverted index compression JM Luna, A Cano, M Pechenizkiy, S Ventura IEEE transactions on cybernetics 46 (12), 3059-3072, 2016 | 48 | 2016 |
| Evaluation and comparison of open source software suites for data mining and knowledge discovery AH Altalhi, JM Luna, MA Vallejo, S Ventura Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 7 (3 …, 2017 | 45 | 2017 |
| Mining local periodic patterns in a discrete sequence P Fournier-Viger, P Yang, RU Kiran, S Ventura, JM Luna Information Sciences 544, 519-548, 2021 | 43 | 2021 |
Sebastián Ventura (ORCID: 0000-000...Professor of Computing and Artificial Intelligence, University of Cordoba (RoR:05yc77b46)Verified email at uco.es
