Association Rule Mining Bibliography

Journal articles

  1. J.M. Luna , J.R. Romero and S. Ventura. On the Adaptability of G3PARM to the Extraction of Rare Association Rules. Knowledge and Information Systems, Volume 38, Issue 2 (2014), Page 391-418.
  2. J.M. Luna , J.R. Romero and S. Ventura. Grammar-Based Multi-Objective Algorithms for Mining Association Rules. Data & Knowledge Engineering, Volume 86, Page 19-37, 2013.
  3. C. Romero , A. Zafra , J.M. Luna and S. Ventura. Association rule mining using genetic programming to provide feedback to instructors from multiple-choice quiz data. Expert Systems, Volume 30, Issue 2 (May 2013), Page 162-172.
  4. J.L. Olmo , J.M. Luna , J.R. Romero and S. Ventura. Mining association rules with single and multi-objective grammar guided ant programming. Integrated Computer Aided Engineering, Volume 20, Issue 3 (2013), Page 217-234.
  5. A. Cano , J.M. Luna , and S. Ventura. High Performance Evaluation of Evolutionary-Mined Association Rules on GPUs. Journal of Supercomputing, Volume 66, Issue 3 (2013), Page 1438-1461.
  6. J.M. Luna , J.R. Romero and S. Ventura. Design and Behaviour Study of a Grammar Guided Genetic Programming Algorithm for Mining Association Rules. Knowledge and Information Systems, Volume 32, Issue 1 (2012), Page 53-76.
  7. C. Romero , J.M. Luna , J.R. Romero and S. Ventura. RM-Tool: A framework for discovering and evaluating association rules. Advances in Engineering Software, 42 (8), pages 566-576, 2011.
  8. E. Garcia , C. Romero , S. Ventura and C. De Castro . A collaborative educational association rule mining tool. The Internet and Higher Education, 14 (2), pages 77-88, 2011.
  9. E. Garcia , C. Romero , S. Ventura and C. De Castro . An architecture for making recommendations to courseware authors using association rule mining and collaborative filtering. User Modeling and User-Adapted Interaction, 19 (1-2), pages 99-132, 2009.

Conference contributions

  1. J.M. Luna , J.R. Romero , C. Romero and S. Ventura. A Genetic Programming Free-Parameter Algorithm for Mining Association Rules, Proceedings of the 12th International Conference on Intelligent Systems Design and Applications, ISDA 2012, pag: 64-69, ISBN: 978-1-4673-5118-8.
  2. J.L. Olmo , J.M. Luna , J.R. Romero and S. Ventura. Association Rule Mining using a Multi-Objective Grammar-Based Ant Programming Algorithm, Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, ISDA 2011, pag: 971-977, ISBN: 978-1-4577-1675-1.
  3. J.M. Luna , J.R. Romero and S.Ventura. Mining and Representing Rare Association Rules through the Use of Genetic Programming, Proceedings of the 3rd World Congress on Nature and Biologically Inspired Computing, NaBIC 2011, pag: 86-91, ISBN: 978-145771123-7.
  4. J.M. Luna , J.R. Romero and S. Ventura. Analysis fo the Effectiveness of G3PARM Algorithm, Proceedings of the 5th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2010, pag: 27-34, ISBN: 978-3-642-13802-7
  5. J.M. Luna , J.R. Romero and S. Ventura. G3PARM: A Grammar Guided Genetic Programming Algorithm for Mining Association Rules, Proceedings of the IEEE Congress on Evolutionary Computation, IEEE CEC 2010, pag: 2586-2593, ISBN: 978-1-4244-6910-8.
  6. C. Romero , J.M. Luna , J.R. Romero and S. Ventura. Mining Rare Association Rules from e-Learning Data, Proceedings of the 3rd International Conference on Educational Data Mining, EDM 2010, pag: 171-180, ISBN: 978-0-615-37529-8.
  7. C. Romero , S. Ventura, E. Vasilyeva and M. Pechenizkiy . Class association rule mining from students' test data, Proceedings of the 3rd International Conference on Educational Data Mining, EDM 2010, pag: 171-180, ISBN: 978-0-615-37529-8.
  8. E. Garcia , C. Romero , S. Ventura and C. De Castro . Evaluating web based instructional models using association rule mining, Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2009, pag: 16-29, ISBN: 978-364202246-3.
  9. E. Garcia , C. Romero , S. Ventura and T. Calders . Drawbacks and solutions of applying association rule mining in learning management systems, Proceedings of the International Workshop on Applying Data Mining in e-Learning, ADML 2007, pag: 13-22, ISSN: 1613007.