RDFTensor: 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.

Version: 1.0
Depends: R (≥ 3.2.0), Matrix, methods, pracma
Published: 2018-11-27
Author: Abdelmoneim Amer Desouki
Maintainer: Abdelmoneim Amer Desouki <desouki at mail.upb.de>
License: GPL-3
NeedsCompilation: no
CRAN checks: RDFTensor results

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Reference manual: RDFTensor.pdf
Package source: RDFTensor_1.0.tar.gz
Windows binaries: r-devel: RDFTensor_1.0.zip, r-release: RDFTensor_1.0.zip, r-oldrel: RDFTensor_1.0.zip
OS X binaries: r-release: RDFTensor_1.0.tgz, r-oldrel: RDFTensor_1.0.tgz

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