/**
   * 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);
  }
  /**
   * Build a rating matrix from the rating data. Each user's ratings are first normalized by
   * subtracting a baseline score (usually a mean).
   *
   * @param userMapping The index mapping of user IDs to column numbers.
   * @param itemMapping The index mapping of item IDs to row numbers.
   * @return A matrix storing the <i>normalized</i> user ratings.
   */
  private RealMatrix createRatingMatrix(IdIndexMapping userMapping, IdIndexMapping itemMapping) {
    final int nusers = userMapping.size();
    final int nitems = itemMapping.size();

    // Create a matrix with users on rows and items on columns
    logger.info("creating {} by {} rating matrix", nusers, nitems);
    RealMatrix matrix = MatrixUtils.createRealMatrix(nusers, nitems);

    // populate it with data
    Cursor<UserHistory<Event>> users = userEventDAO.streamEventsByUser();
    try {
      for (UserHistory<Event> user : users) {
        // Get the row number for this user
        int u = userMapping.getIndex(user.getUserId());
        MutableSparseVector ratings = Ratings.userRatingVector(user.filter(Rating.class));
        MutableSparseVector baselines = MutableSparseVector.create(ratings.keySet());
        baselineScorer.score(user.getUserId(), baselines);
        // TODO Populate this user's row with their ratings, minus the baseline scores
        for (VectorEntry entry : ratings.fast(State.SET)) {
          long itemid = entry.getKey();
          int i = itemMapping.getIndex(itemid);
          double rating = entry.getValue();
          double baseline = baselines.get(itemid);
          matrix.setEntry(u, i, rating - baseline);
        }
      }
    } finally {
      users.close();
    }

    return matrix;
  }