Keywords: Data Mining [rss]
2013
[20] The DATA Bonanza: Improving Knowledge Discovery for Science, Engineering and Business (M.P. Atkinson, R. Baxter, P. Brezany, O. Corcho, M. Galea, J. van Hemert, M. Parsons, D. Snelling), (Albert Y. Zamaya (series), ed.), John Wiley & Sons Ltd., 2013. [bib]
2012
[19] EnzML: multi-label prediction of enzyme classes using InterPro signatures (L. De Ferrari, S. Aitken, J. van Hemert, I. Goryanin), In BMC Bioinformatics, volume 13, 2012. [bib]
2011
[18] A Generic Parallel Processing Model for Facilitating Data Mining and Integration (L. Han, C.S. Liew, Malcolm P.A., J.I. van Hemert), In Parallel Computing, Elsevier, volume 37, 2011. [bib] [pdf]
[17] Automatically Identifying and Annotating Mouse Embryo Gene Expression Patterns (L. Han, J.I. van Hemert, R.A. Baldock), In Bioinformatics, volume 27, 2011. [bib] [pdf] [doi]
2009
[16] Automating Gene Expression Annotation for Mouse Embryo (L. Han, J.I. van Hemert, R.A. Baldock, M.P. Atkinson), In Advanced Data Mining and Applications, 5th International Conference, Springer, volume 5678, 2009. [bib] [doi]
[15] Using architectural simulation models to aid the design of data intensive application (J. Fernández, L. Han, A. Nuñez, J. Carretero, J.I. van Hemert), In Third International Conference on Advanced Engineering Computing and Applications in Sciences, 2009. [bib]
[14] A model of social collaboration in Molecular Biology knowledge bases (L. De Ferrari, S. Aitken, J.I. van Hemert, I. Goryanin), In Proceedings of the 6th Conference of the European Social Simulation Association (ESSA'09) (Bruce Edmonds, Nigel Gilbert, eds.), European Social Simulation Association, 2009. [bib]
[13] An E-infrastructure to Support Collaborative Embryo Research (A. Barker, J.I. van Hemert, R.A. Baldock, M.P. Atkinson), In Cluster Computing and the Grid, IEEE Computer Society, 2009. [bib] [doi]
[12] A distributed architecture for data mining and integration (M.P. Atkinson, J.I. van Hemert, L. Han, A. Hume, C.S. Liew), In DADC '09: Proceedings of the second international workshop on Data-aware distributed computing, ACM, 2009. [bib] [pdf] [doi]
2008
[11] A Novel Visual Discriminator for Network Traffic Patterns (L. Han, J.I. van Hemert), In Proceedings of the International Conference on Advanced Engineering Computing and Applications in Sciences, 2008. [bib] [doi]
[10] Matching Spatial Regions with Combinations of Interacting Gene Expression Patterns (J.I. van Hemert, R.A. Baldock), In Proceedings of the 2nd International Conference on BioInformatics Research and Development (M. Elloumi, \emphet al., eds.), Springer, 2008. [bib]
2007
[9] Mining spatial gene expression data for association rules (J.I. van Hemert, R.A. Baldock), In Proceedings of the 1st International Conference on BioInformatics Research and Development (S. Hochreiter, R. Wagner, eds.), Springer, 2007. [bib] [pdf]
2002
[8] Application of Evolutionary Computation to Constraint Satisfaction and Data Mining (J.I. van Hemert), PhD thesis, Leiden University, 2002. (ISBN: 90-6734-057-X) [bib]
2001
[7] Evolutionary Computation in Constraint Satisfaction and Machine Learning --- An abstract of my PhD. (J.I. van Hemert), In Proceedings of the Brussels Evolutionary Algorithms Day (BEAD-2001) (Anne Defaweux, Bernard Manderick, Tom Lenearts, Johan Parent, Piet van Remortel, eds.), Vrije Universiteit Brussel (VUB), 2001. [bib]
[6] Adaptive Genetic Programming Applied to New and Existing Simple Regression Problems (J. Eggermont, J.I. van Hemert), In Genetic Programming (J. Miller, M. Tomassini, P.L. Lanzi, C. Ryan, A.G.B. Tettamanzi, W.B. Langdon, eds.), Springer, 2001. [bib]
2000
[5] Stepwise Adaptation of Weights for Symbolic Regression with Genetic Programming (J. Eggermont, J.I. van Hemert), In Proceedings of the Twelfth Belgium/Netherlands Conference on Artificial Intelligence (A. van den Bosch, H. Weigand, eds.), 2000. [bib]
1999
[4] Comparing genetic programming variants for data classification (J. Eggermont, A.E. Eiben, J.I. van Hemert), In Proceedings of the Eleventh Belgium/Netherlands Conference on Artificial Intelligence (E. Postma, M. Gyssens, eds.), 1999. [bib]
[3] A comparison of genetic programming variants for data classification (J. Eggermont, A.E. Eiben, J.I. van Hemert), In Advances in Intelligent Data Analysis (D.J. Hand, J.N. Kok, M.R. Berthold, eds.), Springer, 1999. [bib]
[2] Adapting the Fitness Function in GP for Data Mining (J. Eggermont, A.E. Eiben, J.I. van Hemert), In Genetic Programming (R. Poli, P. Nordin, W.B. Langdon, T.C. Fogarty, eds.), Springer, 1999. [bib]
1998
[1] Applying Adaptive Evolutionary Algorithms to Hard Problems (J.I. van Hemert), Master's thesis, Leiden University, 1998. [bib]
Powered by bibtexbrowser