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Fernando Benites

Contact

Address

Universität Konstanz

Fachbereich Informatik und Informationswissenschaft

Box 712

78457 Konstanz, Germany

Room Z 723
Phone (+49) 07531 88-4765
Fax (+49) 07531 88-5132
E-Mail fernando.benites(at)uni-konstanz.de
Portrait

Curriculum Vitae

  • 2007

Diploma on Studies of Applied Computer Science in Natural Sciences at the University of Bielefeld

  • 7.2007-7.2009

Software Developer for Bitfarm GmbH

  • since 8.2009

Research assistant on the Project DAMIART

Research Interests:

  • Adaptive Resonance Theory
  • Fuzzy Neural Networks
  • Text, Gene-Protein, and  Hierarchical Multi-Label Classification

Publications

Benites, Fernando, Sapozhnikova, Elena P., Hierarchical interestingness measures for association rules with generalization on both antecedent and consequent sides, Pattern Recognition Letters, vol. 65, pp. 197 - 203, 2015; Doi: http://dx.doi.org/10.1016/j.patrec.2015.07.027, BibTeX.
Benites, Fernando, Sapozhnikova, Elena P., Improving Multi-label Classification by Means of Cross-Ontology Association Rules. In: Proceedings of the 17th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, October 7-9, 2015, Series CEUR Workshop Proceedings, CEUR-WS.org, Doi: http://ceur-ws.org/, 2015; BibTeX.
Benites, Fernando, Sapozhnikova, Elena P., HARAM: a Hierarchical ARAM neural network for large-scale text classification. In: Proceedings of 2015 IEEE International Conference on Data Mining Workshops, The 3rd International Workshop on High Dimensional Data Mining (HDM’15), 2015; BibTeX.
Benites, Fernando, Sapozhnikova, Elena, Evaluation of Hierarchical Interestingness Measures for Mining Pairwise Generalized Association Rules, IEEE Transactions on Knowledge and Data Engineering, vol. 26, no. 12, pp. 3012-3025, 2014; Doi: 10.1109/TKDE.2014.2320722, BibTeX.
Benites, Fernando, Sapozhnikova, Elena P., Using Semantic Data Mining for Classification Improvement and Knowledge Extraction. In: Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014, Seidl, Thomas, Hassani, Marwan, Beecks, Christian, Series CEUR Workshop Proceedings, vol. 1226, pp. 150-155, CEUR-WS.org, Doi: http://ceur-ws.org/Vol-1226/paper23.pdf, 2014; BibTeX.
Benites, Fernando, Simon, Svenja, Sapozhnikova, Elena, Mining Rare Associations between Biological Ontologies, PLoS ONE, vol. 9, no. 1, pp. e84475, Public Library of Science, 2014; Doi: 10.1371/journal.pone.0084475, BibTeX.
Benites, Fernando, Sapozhnikova, Elena, Generalized Association Rules for Connecting Biological Ontologies. In: Proceedings of the 4th International Conference on Bioinformatics Models, Methods and Algorithms, Series BIOINFORMATICS 2013, 2013; BibTeX.
Benites, Fernando, Sapozhnikova, Elena, Learning different concept hierarchies and the relations between them from classified data, In: Magdalena, R., Martínez, M., Martínez, J.M., Escandell, P., Vila, J., Intel. Data Analysis for Real-Life Applications: Theory and Practice. IGI Global, Doi: 10.4018/978-1-4666-1806-0.ch002, 2012; BibTeX.
Brucker, Florian, Benites, Fernando, Sapozhnikova, Elena, Multi-label classification and extracting predicted class hierarchies, Pattern Recognition, vol. 44, no. 3, pp. 724 - 738, 2011; Doi: DOI: 10.1016/j.patcog.2010.09.010, BibTeX.
Brucker, Florian, Benites, Fernando, Sapozhnikova, Elena, An Empirical Comparison of Flat and Hierarchical Performance Measures for Multi-Label Classification with Hierarchy Extraction, In: Andreas, König,, Andreas, Dengel,, Knut, Hinkelmann,, Koichi, Kise,, RobertJ., Howlett,, LakhmiC., Jain,, Knowledge-Based and Intelligent Information and Engineering Systems. ( Lecture Notes in Computer Science , Vol. 6881 ). Springer Berlin Heidelberg, pp. 579-589, Doi: 10.1007/978-3-642-23851-2_59, 2011; BibTeX.
Benites, Fernando, Brucker, Florian, Sapozhnikova, Elena, Multi-Label Classification by ART-based Neural Networks and Hierarchy Extraction. In: Proceedings of the International Joint Conference on Neural Network 2010, International Joint Conference on Neural Networks of the IEEE World Congress on Computational Intelligence (IJCNN - WCCI), 2010; BibTeX.