2018
|
Reyes, O; Moyano, J M; Luna, J M; Ventura, S A gene expression programming method for multi-target regression Inproceedings Proceedings of the International Conference on Learning and Optimization
Algorithms: Theory and Applications, LOPAL 2018, Rabat, Morocco,
May 2-5, 2018., pp. 2:1–2:6, 2018. Links | BibTeX | Tags: Evolutionary Algorithms, Gene Expression Programming (GEP), Multi-label Learning @inproceedings{Reyes2018a_LOPAL,
title = {A gene expression programming method for multi-target regression},
author = {Reyes, O. and Moyano, J. M. and Luna, J. M. and Ventura, S.},
url = {http://doi.acm.org/10.1145/3230905.3230910},
doi = {10.1145/3230905.3230910},
year = {2018},
date = {2018-01-01},
booktitle = {Proceedings of the International Conference on Learning and Optimization
Algorithms: Theory and Applications, LOPAL 2018, Rabat, Morocco,
May 2-5, 2018.},
pages = {2:1--2:6},
keywords = {Evolutionary Algorithms, Gene Expression Programming (GEP), Multi-label Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Reyes, O; Luna, J M; Moyano, J M; Pérez, E; Ventura, S Resolución de Problemas Biomédicos mediante Técnicas de Extracción de Conocimiento Inproceedings XVIII Conferencia de la Asociación Española para la Inteligencia Artificial, CAEPIA 2018, pp. 1252–1257, 2018. Links | BibTeX | Tags: Medical Data Mining @inproceedings{Reyes2018b_CAEPIA,
title = {Resoluci\'{o}n de Problemas Biom'{e}dicos mediante T'{e}cnicas de Extracci\'{o}n de Conocimiento},
author = {Reyes, O. and Luna, J. M. and Moyano, J. M. and P'{e}rez, E. and Ventura, S.},
url = {https://sci2s.ugr.es/caepia18/proceedings/docs/CAEPIA2018_paper_102.pdf},
year = {2018},
date = {2018-01-01},
booktitle = {XVIII Conferencia de la Asociaci\'{o}n Espa\~{n}ola para la Inteligencia Artificial, CAEPIA 2018},
pages = {1252--1257},
keywords = {Medical Data Mining},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Luna, J M; Ondra, M; Fardoun, H M; Ventura, S Optimization of quality measures in association rule mining: an empirical study Journal Article International Journal of Computational Intelligence Systems, 12 (1), pp. 59–78, 2018. Links | BibTeX | Tags: Association Rule Mining, Evolutionary Algorithms, Pattern Mining, Unsupervised Learning @article{DBLP:journals/ijcisys/LunaOFV18,
title = {Optimization of quality measures in association rule mining: an empirical study},
author = {Luna, J. M. and Ondra, M. and Fardoun, H. M. and Ventura, S.},
url = {https://www.atlantis-press.com/journals/ijcis/25905182},
year = {2018},
date = {2018-01-01},
journal = {International Journal of Computational Intelligence Systems},
volume = {12},
number = {1},
pages = {59--78},
keywords = {Association Rule Mining, Evolutionary Algorithms, Pattern Mining, Unsupervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Pérez, E; González, L D; Sánchez, L M; Reyes, O; Ventura, S JCLAL 2.0: mejoras y nuevas funcionalidades en la herramienta Java de código abierto para el aprendizaje activo Inproceedings XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA), Granada, Spain, 2018. Links | BibTeX | Tags: Active Learning, Scalability, Software Design and Development, Spark @inproceedings{Perez2018,
title = {JCLAL 2.0: mejoras y nuevas funcionalidades en la herramienta Java de c\'{o}digo abierto para el aprendizaje activo},
author = {P'{e}rez, E. and Gonz\'{a}lez, L. D. and S\'{a}nchez, L. M. and Reyes, O. and Ventura, S.},
url = {https://sci2s.ugr.es/caepia18/proceedings/docs/CAEPIA2018_TAMIDA6.pdf},
year = {2018},
date = {2018-01-01},
booktitle = {XVIII Conferencia de la Asociaci\'{o}n Espa\~{n}ola para la Inteligencia Artificial (CAEPIA)},
address = {Granada, Spain},
keywords = {Active Learning, Scalability, Software Design and Development, Spark},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Reyes, O; Ventura, S Evolutionary Strategy to perform Batch-Mode Active Learning on Multi-Label Data Journal Article ACM Transactions on Intelligent Systems and Technology, 9 (4), pp. 46–1, 2018. Links | BibTeX | Tags: Active Learning, Evolutionary Algorithms, Multi-label Learning @article{Reyes2018a,
title = {Evolutionary Strategy to perform Batch-Mode Active Learning on Multi-Label Data},
author = {Reyes, O. and Ventura, S.},
url = {https://dl.acm.org/citation.cfm?doid=3183892.3161606},
year = {2018},
date = {2018-01-01},
journal = {ACM Transactions on Intelligent Systems and Technology},
volume = {9},
number = {4},
pages = {46--1},
keywords = {Active Learning, Evolutionary Algorithms, Multi-label Learning},
pubstate = {published},
tppubtype = {article}
}
|
Reyes, O; Altalhi, A H; Ventura, S Statistical comparisons of active learning strategies over multiple datasets Journal Article Knowledge-Based Systems, 145 , pp. 274–288, 2018. Links | BibTeX | Tags: @article{Reyes2018c,
title = {Statistical comparisons of active learning strategies over multiple datasets},
author = {Reyes, O. and Altalhi, A. H. and Ventura, S.},
url = {https://www.sciencedirect.com/science/article/abs/pii/S0950705118300492},
year = {2018},
date = {2018-01-01},
journal = {Knowledge-Based Systems},
volume = {145},
pages = {274--288},
publisher = {Elsevier keywords = Actrive Learning},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Gahete, M D; del Rio-Moreno, M; Alors-Perez, E; Reyes, O; Camargo A., Delgado-Lista J; Lopez-Miranda, J; Castaño, J P; Luque, R M Identification of an Altered Spliceosome-Associated Fingerprint As an Early, Predictive Event For the Development of Type 2 Diabetes In High-Risk Patients Inproceedings Endocrine Society Annual Meeting, USA, 2018. BibTeX | Tags: Medical Data Mining @inproceedings{Reyes2018d,
title = {Identification of an Altered Spliceosome-Associated Fingerprint As an Early, Predictive Event For the Development of Type 2 Diabetes In High-Risk Patients},
author = {Gahete, M. D. and del Rio-Moreno, M. and Alors-Perez, E. and Reyes, O. and Camargo, A., Delgado-Lista, J. and Lopez-Miranda, J. and Casta\~{n}o, J. P. and Luque, R. M.},
year = {2018},
date = {2018-01-01},
booktitle = {Endocrine Society Annual Meeting, USA},
keywords = {Medical Data Mining},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Reyes, O; Fardoun, H; Ventura, S An ensemble-based method for the selection of instances in the multi-target regression problem Journal Article Integrated Computer-Aided Engineering, 25 (4), pp. 305–320, 2018. Links | BibTeX | Tags: Instance Selection, Multi-target Regression @article{Reyes2018f,
title = {An ensemble-based method for the selection of instances in the multi-target regression problem},
author = {Reyes, O. and Fardoun, H. and Ventura, S.},
url = {https://doi.org/10.3233/ICA-180581},
year = {2018},
date = {2018-01-01},
journal = {Integrated Computer-Aided Engineering},
volume = {25},
number = {4},
pages = {305--320},
keywords = {Instance Selection, Multi-target Regression},
pubstate = {published},
tppubtype = {article}
}
|
Gahete, M; del Rio-Moreno, M; Camargo, A; Alcala-Diaz, J F; Alors-Perez, E; Delgado-Lista, J; Reyes, O; Ventura, S; Perez-Martínez, P; Castaño, J P Changes in Splicing Machinery Components Influence, Precede, and Early Predict the Development of Type 2 Diabetes: From the CORDIOPREV Study Journal Article EBioMedicine, 37 , pp. 356–365, 2018. Links | BibTeX | Tags: Feature Selection, Medical Data Mining @article{Reyes2018g,
title = {Changes in Splicing Machinery Components Influence, Precede, and Early Predict the Development of Type 2 Diabetes: From the CORDIOPREV Study},
author = {Gahete, M. and del Rio-Moreno, M. and Camargo, A. and Alcala-Diaz, J. F. and Alors-Perez, E. and Delgado-Lista, J. and Reyes, O. and Ventura, S. and Perez-Mart\^{i}nez, P. and Casta\~{n}o, J. P.},
url = {https://www.sciencedirect.com/science/article/pii/S2352396418304791},
year = {2018},
date = {2018-01-01},
journal = {EBioMedicine},
volume = {37},
pages = {356--365},
publisher = {Elsevier},
keywords = {Feature Selection, Medical Data Mining},
pubstate = {published},
tppubtype = {article}
}
|
Luna, J M; Reyes, O; del Jesus, M J; Ventura, S Reglas de Asociacion en Datos Multi-Instancia mediante Programacion Genética Gramatical Inproceedings IX Simposio Teoría y Aplicaciones de Minería de Datos, CAEPIA-2018, Granada, España, pp. 815–820, 2018. BibTeX | Tags: Evolutionary Algorithms, Genetic Programming, Multi-instance Learning, Pattern Mining @inproceedings{Reyes2018k,
title = {Reglas de Asociacion en Datos Multi-Instancia mediante Programacion Gen'{e}tica Gramatical},
author = {Luna, J. M. and Reyes, O. and del Jesus, M. J. and Ventura, S.},
year = {2018},
date = {2018-01-01},
booktitle = {IX Simposio Teor\^{i}a y Aplicaciones de Miner\^{i}a de Datos, CAEPIA-2018, Granada, Espa\~{n}a},
pages = {815--820},
keywords = {Evolutionary Algorithms, Genetic Programming, Multi-instance Learning, Pattern Mining},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Reyes, O; Morell, C; Ventura, S Effective active learning strategy for multi-label learning Journal Article Neurocomputing, 273 , pp. 494-508, 2018. Links | BibTeX | Tags: Classification, Multi-label Learning, Scalability, Supervised Learning @article{Reyes2018494,
title = {Effective active learning strategy for multi-label learning},
author = {Reyes, O. and Morell, C. and Ventura, S.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028403971&doi=10.1016%2fj.neucom.2017.08.001&partnerID=40&md5=05e151b407c022b621123a619712e214},
doi = {10.1016/j.neucom.2017.08.001},
year = {2018},
date = {2018-01-01},
journal = {Neurocomputing},
volume = {273},
pages = {494-508},
keywords = {Classification, Multi-label Learning, Scalability, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Guerrero-Enamorado, A; Morell, C; Ventura, S A gene expression programming algorithm for discovering classification rules in the multi-objective space Journal Article International Journal of Computational Intelligence Systems, 11 , pp. 540-559, 2018. Links | BibTeX | Tags: Classification, Genetic Programming @article{Guerrero-Enamorado2018540,
title = {A gene expression programming algorithm for discovering classification rules in the multi-objective space},
author = {Guerrero-Enamorado, A. and Morell, C. and Ventura, S.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045650573&doi=10.2991%2fijcis.11.1.40&partnerID=40&md5=ed025fe6f5c90cb4a35b096447dc94ae},
doi = {10.2991/ijcis.11.1.40},
year = {2018},
date = {2018-01-01},
journal = {International Journal of Computational Intelligence Systems},
volume = {11},
pages = {540-559},
keywords = {Classification, Genetic Programming},
pubstate = {published},
tppubtype = {article}
}
|
Esteban, A; Zafra, A; Romero, C A hybrid multi-criteria approach using a genetic algorithm for recommending courses to university students Inproceedings Proceedings of the 11th International Conference on Educational Data Mining, EDM 2018, 2018. Links | BibTeX | Tags: Educational Data Mining, Educational Recommender Systems @inproceedings{Esteban2018,
title = {A hybrid multi-criteria approach using a genetic algorithm for recommending courses to university students},
author = {Esteban, A. and Zafra, A. and Romero, C.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062778498&partnerID=40&md5=d45a8662c04df6c64b127f7c8ac1c03d},
year = {2018},
date = {2018-01-01},
booktitle = {Proceedings of the 11th International Conference on Educational Data Mining, EDM 2018},
keywords = {Educational Data Mining, Educational Recommender Systems},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Bogarín, A; Cerezo, R; Romero, C Discovering learning processes using inductive miner: A case study with learning management systems (LMSs) [Descubriendo procesos de aprendizaje aplicando inductive miner: Un estudio de caso en learning management systems (LMSs)] Journal Article Psicothema, 30 , pp. 322-329, 2018. Links | BibTeX | Tags: Educational Data Mining @article{Bogar\^{i}n2018322,
title = {Discovering learning processes using inductive miner: A case study with learning management systems (LMSs) [Descubriendo procesos de aprendizaje aplicando inductive miner: Un estudio de caso en learning management systems (LMSs)]},
author = {Bogar\^{i}n, A. and Cerezo, R. and Romero, C.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049974033&doi=10.7334%2fpsicothema2018.116&partnerID=40&md5=51408327ae863377ab53a215a967ee28},
doi = {10.7334/psicothema2018.116},
year = {2018},
date = {2018-01-01},
journal = {Psicothema},
volume = {30},
pages = {322-329},
keywords = {Educational Data Mining},
pubstate = {published},
tppubtype = {article}
}
|
Bogarín, A; Cerezo, R; Romero, C A survey on educational process mining Journal Article Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8 , 2018. Links | BibTeX | Tags: Educational Data Mining @article{Bogar\^{i}n2018,
title = {A survey on educational process mining},
author = {Bogar\^{i}n, A. and Cerezo, R. and Romero, C.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85038557947&doi=10.1002%2fwidm.1230&partnerID=40&md5=d79624bcefd64800070825fd35b19c4d},
doi = {10.1002/widm.1230},
year = {2018},
date = {2018-01-01},
journal = {Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery},
volume = {8},
keywords = {Educational Data Mining},
pubstate = {published},
tppubtype = {article}
}
|
2017
|
García-Martínez, C; Ventura, S Multi-view semi-supervised learning using genetic programming interpretable classification rules Inproceedings Proceedings of the IEEE Congress on Evolutionary Computation, pp. 573-579, San Sebastian, Spain, 2017. BibTeX | Tags: Classification Rules, Grammar-Based Genetic Programming, Multi-view Learning @inproceedings{CGarcia-CEC-2017,
title = {Multi-view semi-supervised learning using genetic programming interpretable classification rules},
author = {Garc\^{i}a-Mart\^{i}nez, C. and Ventura, S.},
year = {2017},
date = {2017-07-07},
booktitle = {Proceedings of the IEEE Congress on Evolutionary Computation},
pages = {573-579},
address = {San Sebastian, Spain},
series = {IEEE CEC 2017},
keywords = {Classification Rules, Grammar-Based Genetic Programming, Multi-view Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Sánchez, O; Moyano, J M; Sánchez, L; Alcalá-Fdez, J Mining association rules in R using the package RKEEL Inproceedings 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 1-6, 2017. Links | BibTeX | Tags: Association Rule Mining, Data Mining Software @inproceedings{8015572,
title = {Mining association rules in R using the package RKEEL},
author = {S\'{a}nchez, O. and Moyano, J. M. and S\'{a}nchez, L. and Alcal\'{a}-Fdez, J.},
url = {https://ieeexplore.ieee.org/abstract/document/8015572/},
doi = {10.1109/FUZZ-IEEE.2017.8015572},
year = {2017},
date = {2017-07-01},
booktitle = {2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)},
pages = {1-6},
keywords = {Association Rule Mining, Data Mining Software},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Moyano, J M; Gibaja, E; Ventura, S An evolutionary algorithm for optimizing the target ordering in Ensemble of Regressor Chains Inproceedings 2017 IEEE Congress on Evolutionary Computation (CEC), pp. 2015-2021, 2017. Links | BibTeX | Tags: Evolutionary Algorithms, Multi-label Learning, Supervised Learning @inproceedings{7969548,
title = {An evolutionary algorithm for optimizing the target ordering in Ensemble of Regressor Chains},
author = {Moyano, J. M. and Gibaja, E. and Ventura, S.},
url = {https://ieeexplore.ieee.org/abstract/document/7969548/},
doi = {10.1109/CEC.2017.7969548},
year = {2017},
date = {2017-06-01},
booktitle = {2017 IEEE Congress on Evolutionary Computation (CEC)},
pages = {2015-2021},
keywords = {Evolutionary Algorithms, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Maestre-García, F J; García-Martínez, C; Pérez-Ortíz, M; Gutiérrez, P A An Iterated Greedy Algorithm for Improving the Generation of Synthetic Patterns in Imbalanced Learning Inproceedings Proceedings of the International Work-Conference on Artificial Neural Networks: Advances in Computational Intelligence, pp. 513-524, Cadiz, Spain, 2017. BibTeX | Tags: Classification, Metaheuristics, Supervised Learning @inproceedings{FJMaestre-IWANN-2017,
title = {An Iterated Greedy Algorithm for Improving the Generation of Synthetic Patterns in Imbalanced Learning},
author = {Maestre-Garc\^{i}a, F.J. and Garc\^{i}a-Mart\^{i}nez, C. and P'{e}rez-Ort\^{i}z, M. and Guti'{e}rrez, P.A.},
year = {2017},
date = {2017-05-18},
booktitle = {Proceedings of the International Work-Conference on Artificial Neural Networks: Advances in Computational Intelligence},
pages = {513-524},
address = {Cadiz, Spain},
series = {IWANN 2017},
keywords = {Classification, Metaheuristics, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Rodriguez, F J; Glover, F; García-Martínez, C; Martí, R; Lozano, M GRASP with exterior path-relinking and restricted local search for the multidimensional two-way number partitioning problem Journal Article Computers & Operations Research, 78 , pp. 243–254, 2017, ISSN: 03050548. Links | BibTeX | Tags: Bioinspired algorithms, Metaheuristics @article{Rodriguez-2017-COR,
title = {GRASP with exterior path-relinking and restricted local search for the multidimensional two-way number partitioning problem},
author = {Rodriguez, F. J. and Glover, F. and Garc\^{i}a-Mart\^{i}nez, C. and Mart\^{i}, R. and Lozano, M.},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0305054816302209},
doi = {10.1016/j.cor.2016.09.005},
issn = {03050548},
year = {2017},
date = {2017-02-01},
journal = {Computers & Operations Research},
volume = {78},
pages = {243--254},
keywords = {Bioinspired algorithms, Metaheuristics},
pubstate = {published},
tppubtype = {article}
}
|
Arauzo-Azofra, A; Molina-Baena, J; Jiménez-Vílchez, A; Luque, M Using Individual Feature Evaluation to Start Feature Subset Selection Methods for Classification Inproceedings International Conference on Agents and Artificial Intelligence, pp. 607–614, SCITEPRESS doi = 10.5220/0006204406070614 2017. Links | BibTeX | Tags: Classification, Feature Selection @inproceedings{arauzo2017using,
title = {Using Individual Feature Evaluation to Start Feature Subset Selection Methods for Classification},
author = {Arauzo-Azofra, A. and Molina-Baena, J. and Jim'{e}nez-V\^{i}lchez, A. and Luque, M.},
url = {https://www.scitepress.org/papers/2017/62044/62044.pdf},
year = {2017},
date = {2017-01-01},
booktitle = {International Conference on Agents and Artificial Intelligence},
volume = {2},
pages = {607--614},
organization = {SCITEPRESS doi = 10.5220/0006204406070614},
keywords = {Classification, Feature Selection},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Ramírez, A; Parejo, J A; Romero, J R; Segura, S; Ruiz-Cortés, A Evolutionary composition of QoS-aware web services: a many-objective perspective Journal Article Expert Systems with Applications, 72 , pp. 357-370, 2017, ISSN: 0957-4174. Links | BibTeX | Tags: Bioinspired algorithms, Evolutionary Algorithms, Metaheuristics, Multi-objective Optimization, Search-based Software Engineering @article{Ramirez-2017-ESWA,
title = {Evolutionary composition of QoS-aware web services: a many-objective perspective},
author = {Ram\^{i}rez, A. and Parejo, J. A. and Romero, J. R. and Segura, S. and Ruiz-Cort'{e}s, A.},
url = {http://dx.doi.org/10.1016/j.eswa.2016.10.047},
doi = {10.1016/j.eswa.2016.10.047},
issn = {0957-4174},
year = {2017},
date = {2017-01-01},
journal = {Expert Systems with Applications},
volume = {72},
pages = {357-370},
keywords = {Bioinspired algorithms, Evolutionary Algorithms, Metaheuristics, Multi-objective Optimization, Search-based Software Engineering},
pubstate = {published},
tppubtype = {article}
}
|
Ramírez, A; Romero, J R; Ventura, S On the effect of local search in the multi-objective evolutionary discovery of software architectures Inproceedings IEEE Congress on Evolutionary Computation (CEC), pp. 2038–2045, IEEE, 2017. Links | BibTeX | Tags: Bioinspired algorithms, Evolutionary Algorithms, Metaheuristics, Multi-objective Optimization, Search-based Software Engineering @inproceedings{2017-aramirez-cec,
title = {On the effect of local search in the multi-objective evolutionary discovery of software architectures},
author = {Ram\^{i}rez, A. and Romero, J. R. and Ventura, S.},
url = {http://ieeexplore.ieee.org/document/7969551/},
doi = {10.1109/CEC.2017.7969551},
year = {2017},
date = {2017-01-01},
booktitle = {IEEE Congress on Evolutionary Computation (CEC)},
pages = {2038--2045},
publisher = {IEEE},
keywords = {Bioinspired algorithms, Evolutionary Algorithms, Metaheuristics, Multi-objective Optimization, Search-based Software Engineering},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Ramírez, A; Romero, J R; Ventura, S Búsqueda coevolutiva interactiva aplicada al diseño de software Inproceedings XXII Jornadas en Ingeniería del Software y Bases de Datos (JISBD'17), 2017. Links | BibTeX | Tags: Bioinspired algorithms, Evolutionary Algorithms, Metaheuristics, Search-based Software Engineering @inproceedings{2017-aramirez-jisbd,
title = {B\'{u}squeda coevolutiva interactiva aplicada al dise\~{n}o de software},
author = {Ram\^{i}rez, A. and Romero, J. R. and Ventura, S.},
url = {http://hdl.handle.net/11705/JISBD/2017/034},
year = {2017},
date = {2017-01-01},
booktitle = {XXII Jornadas en Ingenier\^{i}a del Software y Bases de Datos (JISBD'17)},
keywords = {Bioinspired algorithms, Evolutionary Algorithms, Metaheuristics, Search-based Software Engineering},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Bardudo, R; Ramírez, A; Romero, J R; Ventura, S Descubrimiento de patrones de diseño basado en buenas prácticas: modelo y discusión Inproceedings XXII Jornadas en Ingeniería del Software y Bases de Datos (JISBD'17), 2017. Links | BibTeX | Tags: Evolutionary Algorithms, Grammar-Based Genetic Programming, Pattern Mining, Search-based Software Engineering @inproceedings{2017-rbarbudo-jisbd,
title = {Descubrimiento de patrones de dise\~{n}o basado en buenas pr\'{a}cticas: modelo y discusi\'{o}n},
author = {Bardudo, R. and Ram\^{i}rez, A. and Romero, J. R. and Ventura, S.},
url = {http://hdl.handle.net/11705/JISBD/2017/035},
year = {2017},
date = {2017-01-01},
booktitle = {XXII Jornadas en Ingenier\^{i}a del Software y Bases de Datos (JISBD'17)},
keywords = {Evolutionary Algorithms, Grammar-Based Genetic Programming, Pattern Mining, Search-based Software Engineering},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Padillo, F; Luna, J M; Ventura, S An evolutionary algorithm for mining rare association rules: A Big Data approach Inproceedings 2017 IEEE Congress on Evolutionary Computation, CEC 2017, Donostia, San Sebastián, Spain, June 5-8, 2017, pp. 2007–2014, 2017. Links | BibTeX | Tags: Association Rule Mining, Big Data Mining, Evolutionary Algorithms, Grammar-Based Genetic Programming, Hadoop, Pattern Mining, Spark, Unsupervised Learning @inproceedings{PadilloLV17,
title = {An evolutionary algorithm for mining rare association rules: A Big Data approach},
author = {Padillo, F. and Luna, J. M. and Ventura, S.},
url = {https://doi.org/10.1109/CEC.2017.7969547},
doi = {10.1109/CEC.2017.7969547},
year = {2017},
date = {2017-01-01},
booktitle = {2017 IEEE Congress on Evolutionary Computation, CEC 2017, Donostia, San Sebasti\'{a}n, Spain, June 5-8, 2017},
pages = {2007--2014},
keywords = {Association Rule Mining, Big Data Mining, Evolutionary Algorithms, Grammar-Based Genetic Programming, Hadoop, Pattern Mining, Spark, Unsupervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Altalhi, A H; Luna, J M; Vallejo, M A; Ventura, S Evaluation and comparison of open source software suites for data mining and knowledge discovery Journal Article Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 7 (3), 2017. Links | BibTeX | Tags: Data Mining Software, Data Science @article{AltalhiLVV17,
title = {Evaluation and comparison of open source software suites for data mining and knowledge discovery},
author = {Altalhi, A. H. and Luna, J. M. and Vallejo, M. A. and Ventura, S.},
doi = {10.1002/widm.1204},
year = {2017},
date = {2017-01-01},
journal = {Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery},
volume = {7},
number = {3},
keywords = {Data Mining Software, Data Science},
pubstate = {published},
tppubtype = {article}
}
|
Padillo, F; Luna, J M; Ventura, S Exhaustive search algorithms to mine subgroups on Big Data using Apache Spark Journal Article Progress in Artificial Intelligence, 6 (2), pp. 145–158, 2017. Links | BibTeX | Tags: Big Data Mining, Hadoop, Pattern Mining, Spark, Subgroup Discovery @article{PadilloLV17b,
title = {Exhaustive search algorithms to mine subgroups on Big Data using Apache Spark},
author = {Padillo, F. and Luna, J. M. and Ventura, S.},
doi = {10.1007/s13748-017-0112-x},
year = {2017},
date = {2017-01-01},
journal = {Progress in Artificial Intelligence},
volume = {6},
number = {2},
pages = {145--158},
keywords = {Big Data Mining, Hadoop, Pattern Mining, Spark, Subgroup Discovery},
pubstate = {published},
tppubtype = {article}
}
|
Luna, J M; Castro, C; Romero, C MDM tool: A data mining framework integrated into Moodle Journal Article Computer Applications in Engineering Education, 25 (1), pp. 90–102, 2017. Links | BibTeX | Tags: Data Mining Software, Data Science, Educational Data Mining @article{LunaCR17,
title = {MDM tool: A data mining framework integrated into Moodle},
author = {Luna, J. M. and Castro, C. and Romero, C.},
doi = {10.1002/cae.21782},
year = {2017},
date = {2017-01-01},
journal = {Computer Applications in Engineering Education},
volume = {25},
number = {1},
pages = {90--102},
keywords = {Data Mining Software, Data Science, Educational Data Mining},
pubstate = {published},
tppubtype = {article}
}
|
Luna, J M; Pechenizkiy, M; del Jesus, M J; Ventura, S Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming Journal Article IEEE Transactions on Cybernetics, 99 (PP), pp. 1-15, 2017. Links | BibTeX | Tags: Association Rule Mining, Evolutionary Algorithms, Grammar-Based Genetic Programming, Pattern Mining, Unsupervised Learning @article{LunaIEEE17,
title = {Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming},
author = {Luna, J. M. and Pechenizkiy, M. and del Jesus, M. J. and Ventura, S.},
doi = {10.1109/TCYB.2017.2750919},
year = {2017},
date = {2017-01-01},
journal = {IEEE Transactions on Cybernetics},
volume = {99},
number = {PP},
pages = {1-15},
keywords = {Association Rule Mining, Evolutionary Algorithms, Grammar-Based Genetic Programming, Pattern Mining, Unsupervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Luna, J M; Padillo, F; Pechenizkiy, M; Ventura, S Apriori Versions Based on MapReduce for Mining Frequent Patterns on Big Data Journal Article IEEE Transactions on Cybernetics, 99 (PP), pp. 1-15, 2017. Links | BibTeX | Tags: Association Rule Mining, Big Data Mining, Hadoop, Pattern Mining, Spark, Unsupervised Learning @article{LunaIEEE17b,
title = {Apriori Versions Based on MapReduce for Mining Frequent Patterns on Big Data},
author = {Luna, J. M. and Padillo, F. and Pechenizkiy, M. and Ventura, S.},
doi = {10.1109/TCYB.2017.2751081},
year = {2017},
date = {2017-01-01},
journal = {IEEE Transactions on Cybernetics},
volume = {99},
number = {PP},
pages = {1-15},
keywords = {Association Rule Mining, Big Data Mining, Hadoop, Pattern Mining, Spark, Unsupervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Cano, A An ensemble approach to multi-view multi-instance learning Journal Article Knowledge-Based Systems, 136 , pp. 46-57, 2017. Links | BibTeX | Tags: Classification, Multi-instance Learning, Multi-view Learning @article{2017-KNOSYS-MIMV,
title = {An ensemble approach to multi-view multi-instance learning},
author = {Cano, A.},
url = {http://dx.doi.org/10.1016/j.knosys.2017.08.022},
doi = {10.1016/j.knosys.2017.08.022},
year = {2017},
date = {2017-01-01},
journal = {Knowledge-Based Systems},
volume = {136},
pages = {46-57},
keywords = {Classification, Multi-instance Learning, Multi-view Learning},
pubstate = {published},
tppubtype = {article}
}
|
Gonzalez-Lopez, J; Cano, A; Ventura, S Large-scale multi-label ensemble learning on Spark Inproceedings Proceedings of the 11th IEEE International Conference On Big Data Science And Engineering, pp. 893-900, 2017. BibTeX | Tags: Multi-label Learning, Scalability, Spark @inproceedings{2017-IEEEBIGDATA,
title = {Large-scale multi-label ensemble learning on Spark},
author = {Gonzalez-Lopez, J. and Cano, A. and Ventura, S.},
year = {2017},
date = {2017-01-01},
booktitle = {Proceedings of the 11th IEEE International Conference On Big Data Science And Engineering},
pages = {893-900},
keywords = {Multi-label Learning, Scalability, Spark},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Cano, A; García-Martínez, C; Ventura, S Extremely High-dimensional Optimization with MapReduce: Scaling Functions and Algorithm Journal Article Information Sciences, 415-416 , pp. 110-127, 2017. Links | BibTeX | Tags: Metaheuristics, Scalability @article{2017-INS-REALOPT,
title = {Extremely High-dimensional Optimization with MapReduce: Scaling Functions and Algorithm},
author = {Cano, A. and Garc\^{i}a-Mart\^{i}nez, C. and Ventura, S.},
url = {http://dx.doi.org/10.1016/j.ins.2017.06.024},
doi = {10.1016/j.ins.2017.06.024},
year = {2017},
date = {2017-01-01},
journal = {Information Sciences},
volume = {415-416},
pages = {110-127},
keywords = {Metaheuristics, Scalability},
pubstate = {published},
tppubtype = {article}
}
|
Melki, G; Cano, A; Kecman, V; Ventura, S Multi-Target Support Vector Regression Via Correlation Regressor Chains Journal Article Information Sciences, 415-416 , pp. 53-69, 2017. Links | BibTeX | Tags: Multi-label Learning, Supervised Learning @article{2017-INS-MTR,
title = {Multi-Target Support Vector Regression Via Correlation Regressor Chains},
author = {Melki, G. and Cano, A. and Kecman, V. and Ventura, S.},
url = {http://dx.doi.org/10.1016/j.ins.2017.06.017},
doi = {10.1016/j.ins.2017.06.017},
year = {2017},
date = {2017-01-01},
journal = {Information Sciences},
volume = {415-416},
pages = {53-69},
keywords = {Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Krawczyk, B; McInnes, B; Cano, A Sentiment Classification from Multi-class Imbalanced Twitter Data Using Binarization Inproceedings Proceedings of the 12th International Conference on Hybrid Artificial Intelligent Systems, pp. 26-37, 2017. BibTeX | Tags: Classification, Supervised Learning @inproceedings{2017-HAIS,
title = {Sentiment Classification from Multi-class Imbalanced Twitter Data Using Binarization},
author = {Krawczyk, B. and McInnes, B. and Cano, A.},
year = {2017},
date = {2017-01-01},
booktitle = {Proceedings of the 12th International Conference on Hybrid Artificial Intelligent Systems},
pages = {26-37},
keywords = {Classification, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Triguero, I; González, S; Moyano, J M; García, S; Alcalá-Fdez, J; Luengo, J; Fernández, A; del Jesús, M J; Sánchez, L; Herrera, F KEEL 3.0: an open source software for multi-stage analysis in data mining Journal Article International Journal of Computational Intelligence Systems, 10 (1), pp. 1238-1249, 2017, ISSN: 1875-6883. Links | BibTeX | Tags: Data Mining Software @article{KEEL3,
title = {KEEL 3.0: an open source software for multi-stage analysis in data mining},
author = {Triguero, I. and Gonz\'{a}lez, S. and Moyano, J. M. and Garc\^{i}a, S. and Alcal\'{a}-Fdez, J. and Luengo, J. and Fern\'{a}ndez, A. and del Jes\'{u}s, M. J. and S\'{a}nchez, L. and Herrera, F.},
url = {http://eprints.nottingham.ac.uk/id/eprint/46280},
issn = {1875-6883},
year = {2017},
date = {2017-01-01},
journal = {International Journal of Computational Intelligence Systems},
volume = {10},
number = {1},
pages = {1238-1249},
keywords = {Data Mining Software},
pubstate = {published},
tppubtype = {article}
}
|
Romero, C; Ventura, S Educational data science in massive open online courses Journal Article WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, 7 (1), pp. 1-12, 2017. Links | BibTeX | Tags: Data Science, Educational Data Mining @article{romero2017educational,
title = {Educational data science in massive open online courses},
author = {Romero, C. and Ventura, S.},
doi = {10.1002/widm.1187},
year = {2017},
date = {2017-01-01},
journal = {WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY},
volume = {7},
number = {1},
pages = {1-12},
publisher = {WILEY PERIODICALS, INC ONE MONTGOMERY ST, SUITE 1200, SAN FRANCISCO, CA 94104 USA},
keywords = {Data Science, Educational Data Mining},
pubstate = {published},
tppubtype = {article}
}
|
Bogarín, A; Cerezo, R; Romero, C A survey on educational process mining Journal Article Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2017. Links | BibTeX | Tags: Educational Data Mining @article{bogarin2017survey,
title = {A survey on educational process mining},
author = {Bogar\^{i}n, A. and Cerezo, R. and Romero, C.},
doi = {10.1002/widm.1230},
year = {2017},
date = {2017-01-01},
journal = {Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery},
keywords = {Educational Data Mining},
pubstate = {published},
tppubtype = {article}
}
|
Reyes, O; Morell, C; Ventura, S Effective active learning strategy for multi-label learning Journal Article Neurocomputing, In Press, 2017. Links | BibTeX | Tags: Active Learning, Multi-label Learning @article{REYES2017a,
title = {Effective active learning strategy for multi-label learning},
author = {Reyes, O. and Morell, C. and Ventura, S.},
doi = {https://doi.org/10.1016/j.neucom.2017.08.001},
year = {2017},
date = {2017-01-01},
journal = {Neurocomputing, In Press},
keywords = {Active Learning, Multi-label Learning},
pubstate = {published},
tppubtype = {article}
}
|
Barbudo, R; Ramírez, A; Romero, J R; Ventura, S Descubrimiento de patrones de diseño basado en buenas prácticas: modelo y discusión Inproceedings Actas de XXII Jornadas en Ingenier'ia del Software y Bases de Datos (JISBD'17), 2017. Links | BibTeX | Tags: Evolutionary Algorithms, Grammar-Based Genetic Programming, Software Design and Development @inproceedings{Barbudo-2017-JISBD,
title = {Descubrimiento de patrones de dise\~{n}o basado en buenas pr\'{a}cticas: modelo y discusi\'{o}n},
author = {Barbudo, R. and Ram\^{i}rez, A. and Romero, J. R. and Ventura, S.},
url = {https://biblioteca.sistedes.es/submissions/uploaded-files/JISBD_2017_paper_68.pdf},
year = {2017},
date = {2017-01-01},
booktitle = {Actas de XXII Jornadas en Ingenier'ia del Software y Bases de Datos (JISBD'17)},
keywords = {Evolutionary Algorithms, Grammar-Based Genetic Programming, Software Design and Development},
pubstate = {published},
tppubtype = {inproceedings}
}
|
García-Martínez, C; Gutiérrez, P D; Molina, D; Lozano, M; Herrera, F Since CEC 2005 competition on real-parameter optimisation: a decade of research, progress and comparative analysis's weakness Journal Article Soft Computing, 21 (19), pp. 5573–5583, 2017. Links | BibTeX | Tags: Bioinspired algorithms, Evolutionary Algorithms, Genetic Algorithms, Metaheuristics @article{cgarcia17SinceCEC,
title = {Since CEC 2005 competition on real-parameter optimisation: a decade of research, progress and comparative analysis's weakness},
author = {Garc\^{i}a-Mart\^{i}nez, C. and Guti'{e}rrez, P. D. and Molina, D. and Lozano, M. and Herrera, F.},
doi = {10.1007/s00500-016-2471-9},
year = {2017},
date = {2017-01-01},
journal = {Soft Computing},
volume = {21},
number = {19},
pages = {5573--5583},
keywords = {Bioinspired algorithms, Evolutionary Algorithms, Genetic Algorithms, Metaheuristics},
pubstate = {published},
tppubtype = {article}
}
|
Cano, A; Ventura, S; Cios, K J Multi-Objective Genetic Programming for Feature Extraction and Data Visualization Journal Article Soft Computing, 21 (8), pp. 2069–2089, 2017. Links | BibTeX | Tags: Classification, Genetic Programming @article{Cano-2017-SOCO-MOGPFEV,
title = {Multi-Objective Genetic Programming for Feature Extraction and Data Visualization},
author = {Cano, A. and Ventura, S. and Cios, K. J.},
url = {http://dx.doi.org/10.1007/s00500-015-1907-y},
doi = {10.1007/s00500-015-1907-y},
year = {2017},
date = {2017-01-01},
journal = {Soft Computing},
volume = {21},
number = {8},
pages = {2069--2089},
keywords = {Classification, Genetic Programming},
pubstate = {published},
tppubtype = {article}
}
|
Olex, A; McInnes, B; Cano, A Parsing MetaMap Files in Hadoop Inproceedings American Medical Informatics Association Symposium, 2017. BibTeX | Tags: Hadoop @inproceedings{2017-METAMAP,
title = {Parsing MetaMap Files in Hadoop},
author = {Olex, A. and McInnes, B. and Cano, A.},
year = {2017},
date = {2017-01-01},
booktitle = {American Medical Informatics Association Symposium},
keywords = {Hadoop},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Luque, R M; Gahete, M D; Castaño, J P; Requena-Tapia, M J; Carrasco-Valiente, J; González, T; Moreno, M M; Reyes, O; Herrero-Aguayo, V; Gómez-Gómez, E; others, The Splicing Machinery is Profoundly Deregulated in Prostate Cancer: Pathological and Clinical Implications. Inproceedings 8th IMIBIC young Investigators workshop, Córdoba, Spain, 2017. BibTeX | Tags: Medical Data Mining @inproceedings{Reyes2017,
title = {The Splicing Machinery is Profoundly Deregulated in Prostate Cancer: Pathological and Clinical Implications.},
author = {Luque, R. M. and Gahete, M. D. and Casta\~{n}o, J. P. and Requena-Tapia, M. J. and Carrasco-Valiente, J. and Gonz\'{a}lez, T. and Moreno, M. M. and Reyes, O. and Herrero-Aguayo, V. and G\'{o}mez-G\'{o}mez, E. and others},
year = {2017},
date = {2017-01-01},
booktitle = {8th IMIBIC young Investigators workshop, C\'{o}rdoba, Spain},
keywords = {Medical Data Mining},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Gahete, M D; Luque, R M; Castaño, J P; de la Mata, M; Kineman, R D; Ventura, S; Rodríguez-Perálvarez, M; Reyes, O; Ferrín, G; González-Rubio, S Hepatic Steatosis in Obese Women is Associated with Alterations in Splicing Machinery Components Inproceedings 8th IMIBIC young Investigators workshop; Córdoba, Spain, 2017. BibTeX | Tags: Medical Data Mining @inproceedings{Reyes2017ab,
title = {Hepatic Steatosis in Obese Women is Associated with Alterations in Splicing Machinery Components},
author = {Gahete, M. D. and Luque, R. M. and Casta\~{n}o, J. P. and de la Mata, M and Kineman, R. D. and Ventura, S. and Rodr\^{i}guez-Per\'{a}lvarez, M. and Reyes, O. and Ferr\^{i}n, G. and Gonz\'{a}lez-Rubio, S.},
year = {2017},
date = {2017-01-01},
booktitle = {8th IMIBIC young Investigators workshop; C\'{o}rdoba, Spain},
keywords = {Medical Data Mining},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Moyano, J M; Gibaja, E; Ventura, S MLDA: A tool for analyzing multi-label datasets Journal Article Knowledge-Based Systems, 121 , pp. 1-3, 2017, ISSN: 0950-7051. Links | BibTeX | Tags: Data Mining Software, Data Preprocessing, Multi-label Learning, Multi-view Learning @article{Moyano-2016-KBS,
title = {MLDA: A tool for analyzing multi-label datasets},
author = {Moyano, J. M. and Gibaja, E. and Ventura, S.},
url = {http://dx.doi.org/10.1007/10.1016/j.knosys.2017.01.018},
doi = {10.1016/j.knosys.2017.01.018},
issn = {0950-7051},
year = {2017},
date = {2017-01-01},
journal = {Knowledge-Based Systems},
volume = {121},
pages = {1-3},
keywords = {Data Mining Software, Data Preprocessing, Multi-label Learning, Multi-view Learning},
pubstate = {published},
tppubtype = {article}
}
|
2016
|
Lozano, M; Laguna, M; Martí, R; Rodríguez, F J; García-Martínez, C A genetic algorithm for the minimum generating set problem Journal Article Applied Soft Computing, 48 , pp. 254–264, 2016, ISSN: 15684946. Abstract | Links | BibTeX | Tags: Bioinspired algorithms, Evolutionary Algorithms, Genetic Algorithms, Metaheuristics @article{Lozano2016a,
title = {A genetic algorithm for the minimum generating set problem},
author = {Lozano, M. and Laguna, M. and Mart\^{i}, R. and Rodr\^{i}guez, F. J. and Garc\^{i}a-Mart\^{i}nez, C.},
url = {http://linkinghub.elsevier.com/retrieve/pii/S1568494616303465},
doi = {10.1016/j.asoc.2016.07.020},
issn = {15684946},
year = {2016},
date = {2016-11-01},
journal = {Applied Soft Computing},
volume = {48},
pages = {254--264},
abstract = {Given a set of positive integers S, the minimum generating set problem consists in finding a set of positive integers T with a minimum cardinality such that every element of S can be expressed as the sum of a subset of elements in T. It constitutes a natural problem in combinatorial number theory and is related to some real-world problems, such as planning radiation therapies. We present a new formulation to this problem (based on the terminology for the multiple knapsack problem) that is used to design an evolutionary approach whose performance is driven by three search strategies; a novel random greedy heuristic scheme that is employed to construct initial solutions, a specialized crossover operator inspired by real-parameter crossovers and a restart mechanism that is incorporated to avoid premature convergence. Computational results for problem instances involving up to 100,000 elements show that our innovative genetic algorithm is a very attractive alternative to the existing approaches.},
keywords = {Bioinspired algorithms, Evolutionary Algorithms, Genetic Algorithms, Metaheuristics},
pubstate = {published},
tppubtype = {article}
}
Given a set of positive integers S, the minimum generating set problem consists in finding a set of positive integers T with a minimum cardinality such that every element of S can be expressed as the sum of a subset of elements in T. It constitutes a natural problem in combinatorial number theory and is related to some real-world problems, such as planning radiation therapies. We present a new formulation to this problem (based on the terminology for the multiple knapsack problem) that is used to design an evolutionary approach whose performance is driven by three search strategies; a novel random greedy heuristic scheme that is employed to construct initial solutions, a specialized crossover operator inspired by real-parameter crossovers and a restart mechanism that is incorporated to avoid premature convergence. Computational results for problem instances involving up to 100,000 elements show that our innovative genetic algorithm is a very attractive alternative to the existing approaches. |
Padillo, F; Luna, J M; Ventura, S Subgroup discovery on Big Data: exhaustive methodologies using Map-Reduce Inproceedings Proceedings of the 2016 IEEE Trustcom/BigDataSE/ISPA, pp. 1684–1691, Tianjin, China, 2016. Links | BibTeX | Tags: Big Data Mining, Pattern Mining, Scalability, Spark, Subgroup Discovery @inproceedings{Padillo:BigDataSE16:16,
title = {Subgroup discovery on Big Data: exhaustive methodologies using Map-Reduce},
author = {Padillo, F. and Luna, J. M. and Ventura, S.},
url = {http://dx.doi.org/10.1109/TrustCom/BigDataSE/ISPA.2016.256},
doi = {10.1109/TrustCom/BigDataSE/ISPA.2016.256},
year = {2016},
date = {2016-08-01},
booktitle = {Proceedings of the 2016 IEEE Trustcom/BigDataSE/ISPA},
pages = {1684--1691},
address = {Tianjin, China},
keywords = {Big Data Mining, Pattern Mining, Scalability, Spark, Subgroup Discovery},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Lozano, M; Rodriguez, F J; Peralta, D; García-Martínez, C Randomized greedy multi-start algorithm for the minimum common integer partition problem Journal Article Engineering Applications of Artificial Intelligence, 50 , pp. 226–235, 2016, ISSN: 09521976. Abstract | Links | BibTeX | Tags: Metaheuristics @article{Lozano2016,
title = {Randomized greedy multi-start algorithm for the minimum common integer partition problem},
author = {Lozano, M. and Rodriguez, F. J. and Peralta, D. and Garc\^{i}a-Mart\^{i}nez, C.},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0952197616000415},
doi = {10.1016/j.engappai.2016.01.037},
issn = {09521976},
year = {2016},
date = {2016-04-01},
journal = {Engineering Applications of Artificial Intelligence},
volume = {50},
pages = {226--235},
abstract = {In this paper, we propose a randomized greedy multi-start algorithm for the minimum common integer partition problem. Given k multisets S1,{\l}dots,Sk of positive integers (Si=si1,{\l}dots,sij,{\l}dots,simi), the goal is to find the common integer partition T with minimal cardinality, i.e., a unique and reduced multiset T that, for each Si, it can be partitioned into mi multisets Tj so that the elements in Tj sum to sij. This mathematical problem is reported to appear in computational molecular biology, when assigning orthologs on a genome scale or assembling DNA fingerprints in particular. Our proposed metaheuristic approach constitutes the construction of multiple solutions by a new greedy method that embeds a diversification agent to allow diverse and promising solutions to be reached. Furthermore, we formulate an integer programming model for this problem and show that the CPLEX solver can only solve small instances of the problem. However, computational results for problem instances involving up to 1000 multisets (each one with up to 1000 elements) show that our innovative metaheuristic produces very good feasible solutions in reasonable computing times, arising as a very attractive alternative to the existing approaches.},
keywords = {Metaheuristics},
pubstate = {published},
tppubtype = {article}
}
In this paper, we propose a randomized greedy multi-start algorithm for the minimum common integer partition problem. Given k multisets S1,łdots,Sk of positive integers (Si=si1,łdots,sij,łdots,simi), the goal is to find the common integer partition T with minimal cardinality, i.e., a unique and reduced multiset T that, for each Si, it can be partitioned into mi multisets Tj so that the elements in Tj sum to sij. This mathematical problem is reported to appear in computational molecular biology, when assigning orthologs on a genome scale or assembling DNA fingerprints in particular. Our proposed metaheuristic approach constitutes the construction of multiple solutions by a new greedy method that embeds a diversification agent to allow diverse and promising solutions to be reached. Furthermore, we formulate an integer programming model for this problem and show that the CPLEX solver can only solve small instances of the problem. However, computational results for problem instances involving up to 1000 multisets (each one with up to 1000 elements) show that our innovative metaheuristic produces very good feasible solutions in reasonable computing times, arising as a very attractive alternative to the existing approaches. |