/**
   * Creates a matrix to process genre data and generate the first factor of the proximity matrix
   * needed for a {@code HIRItemScorer}.
   *
   * @param dao The DataAccessObject interfacing with the item data for the model
   * @param gDao The genreDataAccessObject interfacing with the genre data for the model
   */
  public RowStochasticFactorOfProximity(ItemDAO dao, ItemGenreDAO gDao) {
    LongSet items = dao.getItemIds();
    int genreSize = gDao.getGenreSize();
    itemSize = items.size();
    double[][] data = new double[itemSize][genreSize];

    rowStochastic = MatrixUtils.createRealMatrix(data);

    int i = 0;
    LongIterator iter = items.iterator();
    while (iter.hasNext()) {
      long item = iter.nextLong();
      rowStochastic.setRowVector(i, gDao.getItemGenre(item));
      i++;
    }
  }
Ejemplo n.º 2
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 /** Constructs and returns a {@link HIRModel}. */
 @Override
 public HIRModel get() {
   LongSet items = buildContext.getItems();
   LongIterator outer = items.iterator();
   while (outer.hasNext()) {
     final long item1 = outer.nextLong();
     final SparseVector vec1 = buildContext.itemVector(item1);
     LongIterator inner = items.iterator();
     while (inner.hasNext()) {
       final long item2 = inner.nextLong();
       SparseVector vec2 = buildContext.itemVector(item2);
       DAMatrix.putItemPair(item1, vec1, item2, vec2);
     }
   }
   return new HIRModel(
       DAMatrix.buildMatrix(), RSMatrix.RowStochastic(), TFMatrix.ColumnStochastic());
 }
Ejemplo n.º 3
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  private DataSource downsample(DataSource data, LongSet testUsers) throws IOException {
    String fileName = getFileName(data);
    File output = new File(fileName);
    UpToDateChecker checker = new UpToDateChecker();

    checker.addInput(data.lastModified());
    checker.addOutput(output);
    if (!checker.isUpToDate()) {
      RandomOrder<Rating> order = new RandomOrder<Rating>();
      Random rng = new Random();
      // write datasource
      CSVWriter csv = null;
      try {

        csv = CSVWriter.open(output, null);
        Cursor<UserHistory<Rating>> histories =
            data.getUserEventDAO().streamEventsByUser(Rating.class);
        for (UserHistory<Rating> ratings : histories) {
          List<Rating> rats = new ArrayList<Rating>(ratings);
          order.apply(rats, rng);
          for (int i = 0; i < rats.size(); i++) {
            if (!testUsers.contains(ratings.getUserId()) || i < retain) {
              Rating rating = rats.get(i);
              Preference pref = rating.getPreference();
              csv.writeRow(
                  Lists.newArrayList(
                      rating.getUserId(),
                      rating.getItemId(),
                      rating.getValue(),
                      rating.getTimestamp()));
            }
          }
        }
      } finally {
        if (csv != null) {
          csv.close();
        }
      }
    }

    CSVDataSourceBuilder builder = new CSVDataSourceBuilder(data.getName());
    builder.setDomain(data.getPreferenceDomain());
    builder.setFile(output);
    return builder.build();
  }
Ejemplo n.º 4
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 public void close() {
   if (readed != null) readed.close();
 }
Ejemplo n.º 5
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 public boolean addReadedId(long id) {
   return readed.add(id);
 }