View Content-based approach (public)

2011-09-13 20:07 by kidzik | Version 2 | Rating Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star
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Summary

Content-based for recommendation tasks. Needs additional data about items however is independent of other users.

License
CC-BY-SA 3.0
Tags
content-based recommender system
Feature Processing
No processing is required, however method needs expert's data about items.
Parameters
Operating System
independent
Code

% Content based calssification algorithm % argmax_i Y_i'PP % where Y_i is matrix of ratings of all elements of Y equal to i and 0 % elsewhere

% 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 % p - lp norm (default 1) % prop - properties of items

% Copyright (c) Lukasz Kidzinski 2011

Y = reshape(M(y,2),sizeX);

L = zeros(sizeX);
X = zeros(sizeX);
Z = Y';
for i=1:5
    pref = (Z.*(Z == i)) * prop;
    LIKE = pref * prop';
    LIKE = LIKE';
    X(LIKE > L) = i;
    L(LIKE > L) = LIKE(LIKE > L);
end

X(not (X > 1)) = mean(y);
X(X>5) = 5;

end

Software Packages

matlab/octave

Completeness of this item currently: 80%.
Description

(No information yet)

URLs
http://students.mimuw.edu.pl/~lk234151/works/mgr-math.pdf
Publications
    revision 1
    by kidzik on 2011-09-13 20:07
    revision 2
    by kidzik on 2011-09-13 20:07

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    Data | Task | Method | Challenge

    Acknowledgements

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