2015
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Palero, Fernando; Palero, Antonio Gonzalez-Pardo Fernando; Camacho, David Simple gamer interaction analysis through tower defense games Conference 6th International Conference on Computational Collective Intelligence Technologies and Applications (ICCCI 2014), Lecture Notes in Artificial Intelligence of Springer-Verlag, 2015. BibTeX | Tags: Data Analysis, Data Mining, Videogames @conference{2015-PaleroEtAl,
title = {Simple gamer interaction analysis through tower defense games},
author = {Fernando Palero and Antonio Gonzalez-Pardo Fernando Palero and David Camacho},
year = {2015},
date = {2015-01-01},
booktitle = {6th International Conference on Computational Collective Intelligence Technologies and Applications (ICCCI 2014)},
pages = {185-194},
publisher = {Lecture Notes in Artificial Intelligence of Springer-Verlag},
keywords = {Data Analysis, Data Mining, Videogames},
pubstate = {published},
tppubtype = {conference}
}
|
2014
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Gonzalez-Pardo, Antonio; Rosa, Angeles; Camacho, David Behaviour-based identification of student communities in Virtual Worlds Journal Article Computer Science and Information Systems (COMSIS), 11 (1), pp. 195-213, 2014, ISSN: 1820-0214. Links | BibTeX | Tags: Computer-based Education, Data Mining, Normalized Compression Distance, Virtual World @article{2013-GonzalezEtAl-ComSIS,
title = {Behaviour-based identification of student communities in Virtual Worlds},
author = {Antonio Gonzalez-Pardo and Angeles Rosa and David Camacho},
url = {http://aida.ii.uam.es/wp-content/uploads/2014/02/2014-COMSIS-GonzalezEtAl.pdf},
issn = {1820-0214},
year = {2014},
date = {2014-01-01},
journal = {Computer Science and Information Systems (COMSIS)},
volume = {11},
number = {1},
pages = {195-213},
keywords = {Computer-based Education, Data Mining, Normalized Compression Distance, Virtual World},
pubstate = {published},
tppubtype = {article}
}
|
2013
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Bello-Orgaz, Gema; Menéndez, Héctor; Okazaki, Shintaro; Camacho, David Extracting Collective Trends from Twitter Using Social-Based Data Mining Incollection Badica, Nguyen Costin N T; Brezovan, M (Ed.): 5th International Conference on Computational Collective Intelligence (ICCCI 2013), pp. 622–630, Springer-Verlag, 2013. Links | BibTeX | Tags: Classification, Clustering, Collective Trends, Data Mining, Social Network, Twitter @incollection{bello2013extracting,
title = {Extracting Collective Trends from Twitter Using Social-Based Data Mining},
author = {Gema Bello-Orgaz and Héctor Menéndez and Shintaro Okazaki and David Camacho},
editor = {Nguyen N T Costin Badica and M Brezovan},
url = {http://aida.ii.uam.es/wp-content/uploads/2014/12/belloCamachoOkazakiMenendez.pdf},
year = {2013},
date = {2013-09-11},
booktitle = {5th International Conference on Computational Collective Intelligence (ICCCI 2013)},
pages = {622--630},
publisher = {Springer-Verlag},
keywords = {Classification, Clustering, Collective Trends, Data Mining, Social Network, Twitter},
pubstate = {published},
tppubtype = {incollection}
}
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Bello-Orgaz, Gema; Barrero, David.F.; R-Moreno, Maria.D.; Camacho, David Acquisition of Business Intelligence from Human Experience in Route Planning Journal Article Enterprise Information Systems, (Impact Factor: 9.26-Q1), 2013, ISSN: 1751-7575. Links | BibTeX | Tags: Business Intelligence, Data Mining, Genetic Algorithms, Graph Theory @article{Bello-Orgaz:2012:EIS,
title = {Acquisition of Business Intelligence from Human Experience in Route Planning},
author = {Gema Bello-Orgaz and David.F. Barrero and Maria.D. R-Moreno and David Camacho},
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},
number = {Impact Factor: 9.26-Q1},
keywords = {Business Intelligence, Data Mining, Genetic Algorithms, Graph Theory},
pubstate = {published},
tppubtype = {article}
}
|
2012
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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, 7435 , pp. 216-225, Springer Berlin / Heidelberg, 2012, ISSN: 978-3-642-32638-7, (10.1007/978-3-642-32639-4_27). Abstract | Links | BibTeX | Tags: clustering techniques, Data Analysis, Data Mining, Graph Theory @incollection{springerlink:10.1007/978-3-642-32639-4_27,
title = {A Genetic Graph-Based Clustering Algorithm},
author = {Héctor Menéndez and David Camacho},
editor = {Hujun Yin and José Costa and Guilherme Barreto},
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},
keywords = {clustering techniques, Data Analysis, Data Mining, Graph Theory},
pubstate = {published},
tppubtype = {incollection}
}
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. |
2011
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Cebrián, David Camacho Ana Granados Manuel; de Rodriguez, Francisco Borja Reducing the Loss of Information through Annealing Text Distortion Journal Article IEEE Transactions on Knowledge and Data Engineering, 23 (7), pp. 1090-1102, 2011, ISSN: 1041-4347. Links | BibTeX | Tags: Data Mining, pattern clustering, text analysis @article{5582094,
title = {Reducing the Loss of Information through Annealing Text Distortion},
author = {David Camacho Ana Granados Manuel Cebrián and Francisco Borja de Rodriguez},
editor = {IEEE Press},
url = {http://dx.doi.org/10.1109/TKDE.2010.173},
issn = {1041-4347},
year = {2011},
date = {2011-07-01},
journal = {IEEE Transactions on Knowledge and Data Engineering},
volume = {23},
number = {7},
pages = {1090-1102},
keywords = {Data Mining, pattern clustering, text analysis},
pubstate = {published},
tppubtype = {article}
}
|
Bello-Orgaz, Gema; Cajias, Raul; Camacho, David Study on the Impact of Crowd-Based Voting Schemes in the ’Eurovision’ European Contest Inproceedings press, ACM (Ed.): 1st International Conference on Web Intelligence, Mining
and Semantics (WIMS’11), 2011. Links | BibTeX | Tags: Clustering, Data Mining, Graph Theory, Social Networks @inproceedings{BelloCajiasCamacho2011,
title = {Study on the Impact of Crowd-Based Voting Schemes in the ’Eurovision’ European Contest},
author = {Gema Bello-Orgaz and Raul Cajias and David Camacho},
editor = {ACM press},
url = {http://dl.acm.org/citation.cfm?id=1988718
http://aida.ii.uam.es/wp-content/uploads/2012/09/WIMS2011AStudyOnImpact.pdf},
year = {2011},
date = {2011-01-04},
booktitle = {1st International Conference on Web Intelligence, Mining
and Semantics (WIMS’11)},
keywords = {Clustering, Data Mining, Graph Theory, Social Networks},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2004
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Camacho, David; Aler, Ricardo; Cuadrado, Juan Intelligent Agents for Data Mining and Information Retrieval Book Chapter Mohammadian, Masoud (Ed.): Chapter Rule-Based Parsing for Web Data Extracti, pp. 65-87. Chapter 5, Idea Group Publishing, 2004. BibTeX | Tags: Data Mining, Information Theory, Multi-agents systems @inbook{webmantic04,
title = {Intelligent Agents for Data Mining and Information Retrieval},
author = {David Camacho and Ricardo Aler and Juan Cuadrado},
editor = {Masoud Mohammadian},
year = {2004},
date = {2004-01-01},
pages = {65-87. Chapter 5},
publisher = {Idea Group Publishing},
chapter = {Rule-Based Parsing for Web Data Extracti},
keywords = {Data Mining, Information Theory, Multi-agents systems},
pubstate = {published},
tppubtype = {inbook}
}
|
2003
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Camacho, David; López, Miguel A; Aler, Ricardo Semi-Automatic Parsing for Web Knowledge Extraction Inproceedings Applied Informatics, pp. 303-308, 2003. BibTeX | Tags: Data Mining, Semantic Web @inproceedings{DBLP:conf/appinf/CamachoLA03,
title = {Semi-Automatic Parsing for Web Knowledge Extraction},
author = {David Camacho and Miguel A López and Ricardo Aler},
year = {2003},
date = {2003-01-01},
booktitle = {Applied Informatics},
pages = {303-308},
crossref = {DBLP:conf/appinf/2003},
keywords = {Data Mining, Semantic Web},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Camacho, David Thesis: Coordination of planning agents to solve problems in the Web Journal Article AI Commun., 16 (4), pp. 309-311, 2003. BibTeX | Tags: Data Mining, Multi-agents systems @article{DBLP:journals/aicom/Camacho03,
title = {Thesis: Coordination of planning agents to solve problems in the Web},
author = {David Camacho},
year = {2003},
date = {2003-01-01},
journal = {AI Commun.},
volume = {16},
number = {4},
pages = {309-311},
keywords = {Data Mining, Multi-agents systems},
pubstate = {published},
tppubtype = {article}
}
|
2002
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Camacho, David; Molina, José M; Borrajo, Daniel; Aler, Ricardo Solving Travel Problems by Integrating WEB Information with Planning Inproceedings ISMIS, pp. 482-490, 2002. BibTeX | Tags: Data Mining, Planning @inproceedings{DBLP:conf/ismis/CamachoMBA02,
title = {Solving Travel Problems by Integrating WEB Information with Planning},
author = {David Camacho and José M Molina and Daniel Borrajo and Ricardo Aler},
year = {2002},
date = {2002-01-01},
booktitle = {ISMIS},
pages = {482-490},
crossref = {DBLP:conf/ismis/2002},
keywords = {Data Mining, Planning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
