/**
* Build the SVD model.
*
* @return A singular value decomposition recommender model.
*/
@Override
public SVDModel get() {
// Create index mappings of user and item IDs.
// You can use these to find row and columns in the matrix based on user/item IDs.
IdIndexMapping userMapping = IdIndexMapping.create(userDAO.getUserIds());
logger.debug("indexed {} users", userMapping.size());
IdIndexMapping itemMapping = IdIndexMapping.create(itemDAO.getItemIds());
logger.debug("indexed {} items", itemMapping.size());
// We have to do 2 things:
// First, prepare a matrix containing the rating data.
RealMatrix matrix = createRatingMatrix(userMapping, itemMapping);
// Second, compute its factorization
// All the work is done in the constructor
SingularValueDecomposition svd = new SingularValueDecomposition(matrix);
// Third, truncate the decomposed matrix
// TODO Truncate the matrices and construct the SVD model
RealMatrix userMatrix = svd.getU();
RealMatrix weights = svd.getS();
RealMatrix itemMatrix = svd.getV();
userMatrix = userMatrix.getSubMatrix(0, userMatrix.getRowDimension() - 1, 0, featureCount - 1);
weights = weights.getSubMatrix(0, featureCount - 1, 0, featureCount - 1);
itemMatrix = itemMatrix.getSubMatrix(0, itemMatrix.getRowDimension() - 1, 0, featureCount - 1);
return new SVDModel(userMapping, itemMapping, userMatrix, itemMatrix, weights);
}
