Willem Robert van Hage <W.R.van.Hage@vu.nl>
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Different Tensor Factorization (Decomposition) Techniques for
RDF Tensors (Three-Mode-Tensors)
Different Tensor Factorization techniques suitable for RDF Tensors.
RDF Tensors are three-mode-tensors, binary tensors and usually very sparse.
Currently implemented methods are
'RESCAL' Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel (2012) <doi:10.1145/2187836.2187874>,
'NMU' Daniel D. Lee and H. Sebastian Seung (1999) <doi:10.1038/44565>,
'ALS', Alternating Least Squares
'parCube' Papalexakis, Evangelos, C. Faloutsos, and N. Sidiropoulos (2012) <doi:10.1007/978-3-642-33460-3_39>,
'CP_APR' C. Chi and T. G. Kolda (2012) <doi:10.1137/110859063>.
The code is mostly converted from MATLAB and Python implementations of these methods.
The package also contains functions to get Boolean (Binary) transformation of the real-number-decompositions.
These methods also are for general tensors, so with few modifications they can be applied for other types of tensor.

R (>= 3.2.0), Matrix, methods, pracma, doParallel, parallel,
foreach
Different Tensor Factorization techniques suitable for RDF Tensors.
RDF Tensors are three-mode-tensors, binary tensors and usually very sparse.
Currently implemented methods are
'RESCAL' Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel (2012) <doi:10.1145/2187836.2187874>,
'NMU' Daniel D. Lee and H. Sebastian Seung (1999) <doi:10.1038/44565>,
'ALS', Alternating Least Squares
'parCube' Papalexakis, Evangelos, C. Faloutsos, and N. Sidiropoulos (2012) <doi:10.1007/978-3-642-33460-3_39>,
'CP_APR' C. Chi and T. G. Kolda (2012) <doi.org/10.1137/110859063>.
The code is mostly converted from MATLAB and Python implementations of these methods.
The package also contains functions to get Boolean (Binary) transformation of the real-number-decompositions.
These methods also are for general tensors, so with few modifications they can be applied for other types of tensor.