View Recommends via matrix completion (public)

2011-09-13 20:16 by kidzik | Version 1 | Rating Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star
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Summary

More mathematical approach to recommendation problem. No additional data about items and users is needed - just incomplete matrix.

License
CC-BY-SA 3.0
Tags
collaborative-filtering low-rank matrices matrix-completion recommendation
Feature Processing
Parameters
Operating System
independent
Code

%pseudocode

function norm = fobnorm(X) norm = sum(sum(X.*X)) end;

function err = tooptimize(X) err = fubnorm(X-Y); end;

function X = matrixcompletion(y,M,sizeX) % Matrix completion approach to collaborative filtering % finds: argmax_X ||X - Y||_p

% Output % X - matrix to be estimated % Input % y - sampled entries % M - masking operator, applied to vectorized form of X % sizeX - size of matrix to be reconstructed Y = reshape(M(y,2),sizeX);

X = oprimize(tooptimize)

end

Software Packages
Completeness of this item currently: 50%.
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Publications
    revision 1
    by kidzik on 2011-09-13 20:16

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    Acknowledgements

    This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
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