Bello-Orgaz, Gema; Barrero, David.F.; R-Moreno, Maria.D.; Camacho, David Acquisition of Business Intelligence from Human Experience in Route Planning (Article) Enterprise Information Systems, In press, Impact Factor: 3.684-Q1, 2013, ISSN: 1751-7575. (Links | BibTeX) @article{Bello-Orgaz:2012:EIS,
title = {Acquisition of Business Intelligence from Human Experience in Route Planning},
author = {Bello-Orgaz, Gema and Barrero, David.F. and R-Moreno, Maria.D. and Camacho, David},
editor = {Taylor & Francis},
url = {http://aida.ii.uam.es/wp-content/uploads/2012/12/eis.pdf},
issn = {1751-7575},
year = {2013},
date = {2013-06-22},
journal = {Enterprise Information Systems},
volume = {In press},
number = {Impact Factor: 3.684-Q1},
}
|
Gonzalez-Pardo, Antonio; Camacho, David A new CSP graph-based representation for Ant Colony Optimization (Conference) Evolutionary Computation (CEC), 2013 IEEE Congress on, 2013. (BibTeX) @conference{13-GonzalezCamacho-CEC,
title = {A new CSP graph-based representation for Ant Colony Optimization},
author = {Antonio Gonzalez-Pardo and David Camacho},
year = {2013},
date = {2013-05-13},
booktitle = {Evolutionary Computation (CEC), 2013 IEEE Congress on},
pages = {In press},
}
|
Gonzalez-Pardo, Antonio; Rosa, Angeles; Camacho, David Behaviour-based identification of student communities in Virtual Worlds (Article) Computer Science and Information Systems (COMSIS), To appear, 2013. (BibTeX) @article{2013-GonzalezEtAl-ComSIS,
title = {Behaviour-based identification of student communities in Virtual Worlds},
author = {Antonio Gonzalez-Pardo and Angeles Rosa and David Camacho},
year = {2013},
date = {2013-04-22},
journal = {Computer Science and Information Systems (COMSIS)},
volume = {To appear},
}
|
Gonzalez-Pardo, Antonio; Camacho, David Environmental influence in bio-inspired game level solver algorithms (Conference) Proceedings of the 7th International Symposium on Intelligent Distributed Computing - IDC 2013, 2013Studies in Computational Intelligence Springer Berlin Heidelberg, . (BibTeX) @conference{2013-GonzalezCamacho-IDC,
title = {Environmental influence in bio-inspired game level solver algorithms},
author = {Antonio Gonzalez-Pardo and David Camacho},
year = {2013},
date = {2013-04-21},
booktitle = {Proceedings of the 7th International Symposium on Intelligent Distributed Computing - IDC 2013},
pages = {In press},
publisher = {Springer Berlin Heidelberg},
series = {Studies in Computational Intelligence},
}
|
Berns Anke; Gonzalez-Pardo, Antonio; Camacho David Game-like language learning in 3-D virtual environments (Article) Computers & Education, 60, 1, Page(s): 210-220, 2013, ISSN: 0360-1315. (Links | BibTeX) @article{12-AnkeEtAl,
title = {Game-like language learning in 3-D virtual environments},
author = {Berns, Anke; Gonzalez-Pardo, Antonio; Camacho, David},
editor = {Elsevier},
url = {http://aida.ii.uam.es/wp-content/uploads/2012/09/2013-BernsEtAl.pdf},
issn = {0360-1315},
year = {2013},
date = {2013-01-01},
journal = {Computers & Education},
volume = {60},
number = {1},
pages = {210-220},
}
|
David F. Barrero Julio Cesar, María R-Moreno David Camacho A Genetic Tango Attack Against the David-Prasad RFID Ultralightweight Authentication Protocol (Article) Expert Systems, The journal of Knowledge Engineering, Page(s): 1-11, 2012, ISSN: 0952-1976. (Links | BibTeX) @article{DOI: 10.1111/j.1468-0394.2012.00652.x,
title = {A Genetic Tango Attack Against the David-Prasad RFID Ultralightweight Authentication Protocol},
author = {David F. Barrero, Julio Cesar, María D. R-Moreno, David Camacho},
editor = {Wiley-Blackwell},
url = {http://onlinelibrary.wiley.com/doi/10.1111/j.1468-0394.2012.00652.x/pdf},
issn = {0952-1976},
year = {2012},
date = {2012-09-17},
journal = {Expert Systems, The journal of Knowledge Engineering},
pages = {1-11},
}
|
Gonzalez-Pardo, Antonio; Camacho, David Maximal Component detection in graphs using swarm-based and genetic algorithms (Conference) Proceedings of the 6th International Symposium on Intelligent Distributed Computing - IDC 2012, 2012446, Studies in Computational Intelligence Springer Berlin Heidelberg, , ISBN: 978-3-642-32523-6. (BibTeX) @conference{2012-GonzalezCamacho,
title = {Maximal Component detection in graphs using swarm-based and genetic algorithms},
author = {Antonio Gonzalez-Pardo and David Camacho},
isbn = {978-3-642-32523-6},
year = {2012},
date = {2012-07-03},
booktitle = {Proceedings of the 6th International Symposium on Intelligent Distributed Computing - IDC 2012},
volume = {446},
pages = {247 – 252},
publisher = {Springer Berlin Heidelberg},
series = {Studies in Computational Intelligence},
}
|
Bello-Orgaz, Gema; Menendez, Hector; Camacho, David Adaptive K-Means Algorithm for overlapped graph clustering (Article) International Journal of Neural Systems, 22 (Impact Factor:4.284 -Q1), 05, Page(s): 1250018 1--19, 2012, ISSN: 0129-0657. (Links | BibTeX) @article{Bello-Orgaz:2012:IJNS,
title = {Adaptive K-Means Algorithm for overlapped graph clustering},
author = {Bello-Orgaz, Gema and Menendez, Hector and Camacho, David},
url = {http://www.worldscientific.com/doi/abs/10.1142/S0129065712500189
http://aida.ii.uam.es/wp-content/uploads/2012/09/ijns-2012.pdf},
issn = {0129-0657},
year = {2012},
date = {2012-06-18},
journal = {International Journal of Neural Systems},
volume = {22 (Impact Factor:4.284 -Q1)},
number = {05},
pages = {1250018 1--19},
}
|
Menendez, Hector; Bello-Orgaz, Gema; Camacho, David Extracting Behavioural Models from 2010 FIFA World Cup (Article) Journal of Systems Science and Complexity, 26, 1, Page(s): 43-61, 2012, ISSN: 1009-6124. (Abstract | Links | BibTeX) @article{Menendez:2012:JSSC,
title = {Extracting Behavioural Models from 2010 FIFA World Cup},
author = {Menendez, Hector and Bello-Orgaz, Gema and Camacho, David},
editor = {Academy of Mathematics and Systems Science, Chinese Academy of Sciences},
url = {http://link.springer.com/article/10.1007%2Fs11424-013-2289-9},
issn = {1009-6124},
year = {2012},
date = {2012-06-01},
journal = {Journal of Systems Science and Complexity},
volume = {26},
number = {1},
pages = {43-61},
abstract = {The FIFA World Cup™ is the most profitable worldwide event. The FIFA publishes global statistics of this competition which provide global data about the players and teams during the competition. This work is focused on the extraction of behavioural patterns for both, players and teams strategies, through the automated analysis of this dataset. The knowledge and models extracted in this work could be applied to soccer leagues or even it could be oriented to sport betting. However, the main contribution is related to the study on several automatic knowledge extraction techniques, such as clustering methods, and how these techniques can be used to obtain useful behavioural models from a global statistics dataset. The information provided by the clustering algorithms shows similar properties which have been combined to define the models, making the human interpretation of these statistics easier. Finally, the most successful teams strategies have been analysed and compared.},
}
The FIFA World Cup™ is the most profitable worldwide event. The FIFA publishes global statistics of this competition which provide global data about the players and teams during the competition. This work is focused on the extraction of behavioural patterns for both, players and teams strategies, through the automated analysis of this dataset. The knowledge and models extracted in this work could be applied to soccer leagues or even it could be oriented to sport betting. However, the main contribution is related to the study on several automatic knowledge extraction techniques, such as clustering methods, and how these techniques can be used to obtain useful behavioural models from a global statistics dataset. The information provided by the clustering algorithms shows similar properties which have been combined to define the models, making the human interpretation of these statistics easier. Finally, the most successful teams strategies have been analysed and compared. |
Gonzalez-Pardo, Antonio; Varona, Pablo; Camacho, David; de Rodriguez, Francisco Borja Communication by identity in bio-inspired multi-agent systems (Article) International Journal Concurrency and Computation: Practice & Experience. , 2012, 24, Page(s): 589-603, 2012, ISSN: 1532-0626 . (Links | BibTeX) @article{12-Gonzalez-Pardo-CCPE,
title = {Communication by identity in bio-inspired multi-agent systems },
author = {Antonio Gonzalez-Pardo and Pablo Varona and David Camacho and Francisco de Borja Rodriguez},
url = {http://aida.ii.uam.es/wp-content/uploads/2012/03/CCPE-GonzalezPardoEtAl.pdf},
issn = {1532-0626 },
year = {2012},
date = {2012-03-03},
journal = {International Journal Concurrency and Computation: Practice & Experience. },
volume = {2012},
number = {24},
pages = {589-603},
}
|
Menendez, Hector; Bello-Orgaz, Gema; Camacho, David Features selection from high-dimensional web data using clustering analysis (Inproceeding) Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics, Page(s): 20:1--20:9, New York, NY, USA, ACM, 2012, ISSN: 978-1-4503-0915-8. (Links | BibTeX) @inproceedings{Menendez:2012:FSH:2254129.2254155,
title = {Features selection from high-dimensional web data using clustering analysis},
author = {Menendez, Hector and Bello-Orgaz, Gema and Camacho, David},
url = {http://doi.acm.org/10.1145/2254129.2254155},
issn = {978-1-4503-0915-8},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics},
pages = {20:1--20:9},
publisher = {ACM},
address = {New York, NY, USA},
series = {WIMS '12},
}
|
Bello-Orgaz, Gema; R-Moreno, Maria; Camacho, David; Barrero, David Clustering avatars behaviours from virtual worlds interactions (Inproceeding) Proceedings of the 4th International Workshop on Web Intelligence & Communities, Page(s): 4:1--4:7, New York, NY, USA, ACM, 2012, ISSN: 978-1-4503-1189-2. (Links | BibTeX) @inproceedings{Orgaz:2012:CAB:2189736.2189743,
title = {Clustering avatars behaviours from virtual worlds interactions},
author = {Bello-Orgaz, Gema and R-Moreno, Maria D. and Camacho, David and Barrero, David F.},
url = {http://doi.acm.org/10.1145/2189736.2189743},
issn = {978-1-4503-1189-2},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of the 4th International Workshop on Web Intelligence & Communities},
pages = {4:1--4:7},
publisher = {ACM},
address = {New York, NY, USA},
series = {WI&C '12},
}
|
Menéndez, Héctor; Camacho, David A Genetic Graph-Based Clustering Algorithm (Incollection) Yin, Hujun; Costa, José; Barreto, Guilherme (Ed.): Intelligent Data Engineering and Automated Learning - IDEAL 2012, Springer Berlin / Heidelberg, , ISSN: 978-3-642-32638-7. (Abstract | Links | BibTeX) @incollection{springerlink:10.1007/978-3-642-32639-4_27,
title = {A Genetic Graph-Based Clustering Algorithm},
author = {Menéndez, Héctor and Camacho, David},
editor = {Yin, Hujun and Costa, José and Barreto, Guilherme},
note = {10.1007/978-3-642-32639-4_27},
url = {http://dx.doi.org/10.1007/978-3-642-32639-4_27},
issn = {978-3-642-32638-7},
year = {2012},
date = {2012-01-01},
booktitle = {Intelligent Data Engineering and Automated Learning - IDEAL 2012},
volume = {7435},
pages = {216-225},
publisher = {Springer Berlin / Heidelberg},
series = {Lecture Notes in Computer Science},
abstract = {The interest in the analysis and study of clustering techniques have grown since the introduction of new algorithms based on the continuity of the data, where problems related to image segmentation and tracking, amongst others, makes difficult the correct classification of data into their appropriate groups, or clusters. Some new techniques, such as Spectral Clustering (SC), uses graph theory to generate the clusters through the spectrum of the graph created by a similarity function applied to the elements of the database. The approach taken by SC allows to handle the problem of data continuity though the graph representation. Based on this idea, this study uses genetic algorithms to select the groups using the same similarity graph built by the Spectral Clustering method. The main contribution is to create a new algorithm which improves the robustness of the Spectral Clustering algorithm reducing the dependency of the similarity metric parameters that currently affects to the performance of SC approaches. This algorithm, named Genetic Graph-based Clustering (GGC), has been tested with different synthetic and real-world datasets, the experimental results have been compared against classical clustering algorithms like K-Means, EM and SC.},
note = {10.1007/978-3-642-32639-4_27},
}
The interest in the analysis and study of clustering techniques have grown since the introduction of new algorithms based on the continuity of the data, where problems related to image segmentation and tracking, amongst others, makes difficult the correct classification of data into their appropriate groups, or clusters. Some new techniques, such as Spectral Clustering (SC), uses graph theory to generate the clusters through the spectrum of the graph created by a similarity function applied to the elements of the database. The approach taken by SC allows to handle the problem of data continuity though the graph representation. Based on this idea, this study uses genetic algorithms to select the groups using the same similarity graph built by the Spectral Clustering method. The main contribution is to create a new algorithm which improves the robustness of the Spectral Clustering algorithm reducing the dependency of the similarity metric parameters that currently affects to the performance of SC approaches. This algorithm, named Genetic Graph-based Clustering (GGC), has been tested with different synthetic and real-world datasets, the experimental results have been compared against classical clustering algorithms like K-Means, EM and SC. |
