Gerben de Vries
Gerben de Vries
Applied Scientist at Wizenoze.com
Geverifieerd e-mailadres voor wizenoze.com
Titel
Geciteerd door
Geciteerd door
Jaar
Machine learning for vessel trajectories using compression, alignments and domain knowledge
GKD de Vries, M Van Someren
Expert Systems with Applications, 2012
822012
A fast approximation of the Weisfeiler-Lehman graph kernel for RDF data
GKD de Vries
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2013
572013
An integrated approach for visual analysis of a multisource moving objects knowledge base
N Willems, WR van Hage, G de Vries, JHM Janssens, V Malaisé
International Journal of Geographical Information Science 24 (10), 1543-1558, 2010
562010
A collection of benchmark datasets for systematic evaluations of machine learning on the semantic web
P Ristoski, GKD De Vries, H Paulheim
International Semantic Web Conference, 186-194, 2016
552016
Combining ship trajectories and semantics with the simple event model (sem)
WR Van Hage, V Malaisé, G de Vries, G Schreiber, M van Someren
Proceedings of the 1st ACM International Workshop on Events in Multimedia, 73-80, 2009
512009
Substructure counting graph kernels for machine learning from rdf data
GKD De Vries, S De Rooij
Journal of Web Semantics 35, 71-84, 2015
442015
Abstracting and reasoning over ship trajectories and web data with the Simple Event Model (SEM)
WR Van Hage, V Malaisé, GKD de Vries, G Schreiber, MW van Someren
Multimedia Tools and Applications 57 (1), 175-197, 2012
422012
Clustering vessel trajectories with alignment kernels under trajectory compression
G de Vries, M van Someren
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2010
352010
A Fast and Simple Graph Kernel for RDF.
GKD De Vries, S De Rooij
DMoLD 1082, 2013
232013
Comparing vessel trajectories using geographical domain knowledge and alignments
GKD De Vries, WR Van Hage, M Van Someren
2010 IEEE International Conference on Data Mining Workshops, 209-216, 2010
212010
Semi-automatic ontology extension in the maritime domain
GKD De Vries, V Malaisé, M Van Someren, P Adriaans, G Schreiber, ...
Proceedings of the Twentieth Belgian-Dutch Conference on Artificial …, 2008
162008
Machine learning on linked data, a position paper
P Bloem, GKD De Vries
Linked Data for Knowledge Discovery, 69, 2014
112014
Simplifying RDF Data for Graph-Based Machine Learning.
P Bloem, A Wibisono, G De Vries
KNOW@ LOD 1243, 2014
102014
An analysis of alignment and integral based kernels for machine learning from vessel trajectories
GKD De Vries, M Van Someren
Expert systems with applications 41 (16), 7596-7607, 2014
92014
Kernel methods for vessel trajectories
GKD de Vries
SIKS, 2012
92012
Learning a model of ship movements
R Lagerweij, G de Vries, M van Someren
University of Amsterdam, 2009
72009
Unsupervised ship trajectory modeling and prediction using compression and clustering
G de Vries, M van Someren
Proceedings BeneLearn, 7-12, 2009
72009
Generating scientific documentation for computational experiments using provenance
A Wibisono, P Bloem, GKD de Vries, P Groth, A Belloum, M Bubak
International Provenance and Annotation Workshop, 168-179, 2014
52014
Hubble: Linked data hub for clinical decision support
R Hoekstra, S Magliacane, L Rietveld, G De Vries, A Wibisono, ...
Extended Semantic Web Conference, 458-462, 2012
52012
Spatial and semantic reasoning to recognize ship behavior
WR Van Hage, G de Vries, V Malaisé, G Schreiber, M van Someren
Proceedings of the International Semantic Web Conference, Chantilly (VA), 2009
42009
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Artikelen 1–20