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
862012
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
632016
An integrated approach for visual analysis of a multisource moving objects knowledge base
N Willems, WR van Hage, G de Vries, JHM Janssens, V MalaisÚ
International Journal of Geographical Information Science 24 (10), 1543-1558, 2010
582010
A fast approximation of the Weisfeiler-Lehman graph kernel for RDF data
GKD de Vries
Joint European Conference on Machine Learning and Knowledge Discovery iná…, 2013
572013
Combining ship trajectories and semantics with the simple event model (sem)
WR Van Hage, V MalaisÚ, G de Vries, G Schreiber, M van Someren
Proceedings of the 1st ACM International Workshop on Events in Multimedia, 73-80, 2009
522009
Substructure counting graph kernels for machine learning from rdf data
GKD De Vries, S De Rooij
Journal of Web Semantics 35, 71-84, 2015
452015
Abstracting and reasoning over ship trajectories and web data with the Simple Event Model (SEM)
WR Van Hage, V MalaisÚ, GKD de Vries, G Schreiber, MW van Someren
Multimedia Tools and Applications 57 (1), 175-197, 2012
442012
Clustering vessel trajectories with alignment kernels under trajectory compression
G de Vries, M van Someren
Joint European Conference on Machine Learning and Knowledge Discovery iná…, 2010
352010
A Fast and Simple Graph Kernel for RDF.
GKD De Vries, S De Rooij
DMoLD 1082, 2013
252013
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 MalaisÚ, M Van Someren, P Adriaans, G Schreiber, ...
Proceedings of the Twentieth Belgian-Dutch Conference on Artificialá…, 2008
162008
Machine learning on linked data, a position paper
P Bloem, GKD De Vries
Linked Data for Knowledge Discovery, 69, 2014
122014
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 MalaisÚ, G Schreiber, M van Someren
Proceedings of the International Semantic Web Conference, Chantilly (VA), 2009
42009
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Artikelen 1–20