José María Luna (ORCID: 0000-0003-3537-2931)
José María Luna (ORCID: 0000-0003-3537-2931)
Associate Professor of Computing and Artificial Intelligence, University of Cordoba
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Cited by
Cited by
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
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
Mining rare association rules from e-learning data
C Romero, JR Romero, JM Luna, S Ventura
Educational Data Mining 2010, 2010
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
Pattern mining with evolutionary algorithms
S Ventura, JM Luna
Springer, 2016
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
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
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
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
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
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
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
LAIM discretization for multi-label data
A Cano, JM Luna, EL Gibaja, S Ventura
Information Sciences 330 (10), 370–384, 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
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
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
Supervised descriptive pattern mining
S Ventura, JM Luna
Springer International Publishing, 2018
Grammar-based multi-objective algorithms for mining association rules
JM Luna, JR Romero, S Ventura
Data & Knowledge Engineering 86, 19-37, 2013
Mining context-aware association rules using grammar-based genetic programming
JM Luna, M Pechenizkiy, MJ Del Jesus, S Ventura
IEEE transactions on cybernetics 48 (11), 3030-3044, 2017
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
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