| 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 | 551 | 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 | 183 | 2012 |
| Mining rare association rules from e-learning data C Romero, JR Romero, JM Luna, S Ventura Educational Data Mining 2010, 2010 | 114 | 2010 |
| 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 (1), 53-76, 2012 | 79 | 2012 |
| 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 | 73 | 2013 |
| Pattern mining with evolutionary algorithms S Ventura, JM Luna Springer, 2016 | 65 | 2016 |
| 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 | 64 | 2017 |
| 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 (3), 501-513, 2015 | 52 | 2015 |
| 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 | 51 | 2017 |
| 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 | 50 | 2014 |
| High performance evaluation of evolutionary-mined association rules on GPUs A Cano, JM Luna, S Ventura The Journal of Supercomputing 66 (3), 1438-1461, 2013 | 50 | 2013 |
| 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 | 48 | 2019 |
| LAIM discretization for multi-label data A Cano, JM Luna, EL Gibaja, S Ventura Information Sciences 330 (10), 370–384, 2016 | 47 | 2016 |
| 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 | 45 | 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, 2018 | 38 | 2018 |
| 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 | 38 | 2016 |
| Grammar-based multi-objective algorithms for mining association rules JM Luna, JR Romero, S Ventura Data & Knowledge Engineering 86, 19-37, 2013 | 37 | 2013 |
| RM-Tool: A framework for discovering and evaluating association rules C Romero, JM Luna, JR Romero, S Ventura Advances in Engineering Software 42 (8), 566-576, 2011 | 35 | 2011 |
| On the adaptability of G3PARM to the extraction of rare association rules JM Luna, JR Romero, S Ventura Knowledge and information systems 38 (2), 391-418, 2014 | 30 | 2014 |
| A classification module for genetic programming algorithms in JCLEC. A Cano, JM Luna, A Zafra, S Ventura J. Mach. Learn. Res. 16 (1), 491-494, 2015 | 29 | 2015 |
Sebastián VenturaProfessor of Computing and Artificial Intelligence, University of CordobaVerified email at uco.es
