getTensor3m

<p>three columns representing the set of triples (subject, predicate, object).
    Each row representes one triple.</p>

<p>gets a tensor data structure as a set of frontal slices represented as sparse matrices.
   The entities as subject has a different id than object and the size of 
   subject and object modes can be different.</p>

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.

Abdelmoneim Desouki

getTensor3m: getting tensor from triples

Description

Usage

Arguments

Value