Package org.apache.mahout.cf.taste.recommender

Examples of org.apache.mahout.cf.taste.recommender.RecommendedItem


    int size = in.readInt();
    recommended = Lists.newArrayListWithCapacity(size);
    for (int i = 0; i < size; i++) {
      long itemID = Varint.readSignedVarLong(in);
      float value = in.readFloat();
      RecommendedItem recommendedItem = new GenericRecommendedItem(itemID, value);
      recommended.add(recommendedItem);
    }
  }
View Full Code Here


      // nDCG
      // In computing, assume relevant IDs have relevance 1 and others 0
      double cumulativeGain = 0.0;
      double idealizedGain = 0.0;
      for (int i = 0; i < recommendedItems.size(); i++) {
        RecommendedItem item = recommendedItems.get(i);
        double discount = i == 0 ? 1.0 : 1.0 / log2(i + 1);
        if (relevantItemIDs.contains(item.getItemID())) {
          cumulativeGain += discount;
        }
        // otherwise we're multiplying discount by relevance 0 so it doesn't do anything

        // Ideally results would be ordered with all relevant ones first, so this theoretical
View Full Code Here

  public void testRecommender() throws Exception {
    Recommender recommender = buildRecommender();
    List<RecommendedItem> recommended = recommender.recommend(1, 1);
    assertNotNull(recommended);
    assertEquals(1, recommended.size());
    RecommendedItem firstRecommended = recommended.get(0);
    assertEquals(2, firstRecommended.getItemID());
    assertEquals(0.1f, firstRecommended.getValue(), EPSILON);
    recommender.refresh(null);
    recommended = recommender.recommend(1, 1);
    firstRecommended = recommended.get(0);   
    assertEquals(2, firstRecommended.getItemID());
    assertEquals(0.1f, firstRecommended.getValue(), EPSILON);
  }
View Full Code Here

  public void testBestRating() throws Exception {
    Recommender recommender = buildRecommender();
    List<RecommendedItem> recommended = recommender.recommend(1, 1);
    assertNotNull(recommended);
    assertEquals(1, recommended.size());
    RecommendedItem firstRecommended = recommended.get(0);
    // item one should be recommended because it has a greater rating/score
    assertEquals(2, firstRecommended.getItemID());
    assertEquals(0.1f, firstRecommended.getValue(), EPSILON);
  }
View Full Code Here

  public void testMostSimilar() throws Exception {
    ItemBasedRecommender recommender = buildRecommender();
    List<RecommendedItem> similar = recommender.mostSimilarItems(0, 2);
    assertNotNull(similar);
    assertEquals(2, similar.size());
    RecommendedItem first = similar.get(0);
    RecommendedItem second = similar.get(1);
    assertEquals(1, first.getItemID());
    assertEquals(1.0f, first.getValue(), EPSILON);
    assertEquals(2, second.getItemID());
    assertEquals(0.5f, second.getValue(), EPSILON);
  }
View Full Code Here

  public void testMostSimilarToMultiple() throws Exception {
    ItemBasedRecommender recommender = buildRecommender2();
    List<RecommendedItem> similar = recommender.mostSimilarItems(new long[] {0, 1}, 2);
    assertNotNull(similar);
    assertEquals(2, similar.size());
    RecommendedItem first = similar.get(0);
    RecommendedItem second = similar.get(1);
    assertEquals(2, first.getItemID());
    assertEquals(0.85f, first.getValue(), EPSILON);
    assertEquals(3, second.getItemID());
    assertEquals(-0.3f, second.getValue(), EPSILON);
  }
View Full Code Here

  public void testMostSimilarToMultipleExcludeIfNotSimilarToAll() throws Exception {
    ItemBasedRecommender recommender = buildRecommender2();
    List<RecommendedItem> similar = recommender.mostSimilarItems(new long[] {3, 4}, 2);
    assertNotNull(similar);
    assertEquals(1, similar.size());
    RecommendedItem first = similar.get(0);
    assertEquals(0, first.getItemID());
    assertEquals(0.2f, first.getValue(), EPSILON);
  }
View Full Code Here

  public void testMostSimilarToMultipleDontExcludeIfNotSimilarToAll() throws Exception {
    ItemBasedRecommender recommender = buildRecommender2();
    List<RecommendedItem> similar = recommender.mostSimilarItems(new long[] {1, 2, 4}, 10, false);
    assertNotNull(similar);
    assertEquals(2, similar.size());
    RecommendedItem first = similar.get(0);
    RecommendedItem second = similar.get(1);
    assertEquals(0, first.getItemID());
    assertEquals(0.933333333f, first.getValue(), EPSILON);
    assertEquals(3, second.getItemID());
    assertEquals(-0.2f, second.getValue(), EPSILON);
  }
View Full Code Here

  public void testRecommendedBecause() throws Exception {
    ItemBasedRecommender recommender = buildRecommender2();
    List<RecommendedItem> recommendedBecause = recommender.recommendedBecause(1, 4, 3);
    assertNotNull(recommendedBecause);
    assertEquals(3, recommendedBecause.size());
    RecommendedItem first = recommendedBecause.get(0);
    RecommendedItem second = recommendedBecause.get(1);
    RecommendedItem third = recommendedBecause.get(2);
    assertEquals(2, first.getItemID());
    assertEquals(0.99f, first.getValue(), EPSILON);
    assertEquals(3, second.getItemID());
    assertEquals(0.4f, second.getValue(), EPSILON);
    assertEquals(0, third.getItemID());
    assertEquals(0.2f, third.getValue(), EPSILON);
  }
View Full Code Here

    for (Entry<Long,List<RecommendedItem>> entry : recommendations.entrySet()) {
      long userID = entry.getKey();
      List<RecommendedItem> items = entry.getValue();
      assertNotNull(items);
      RecommendedItem item1 = items.get(0);

      if (userID == 1L) {
        assertEquals(1, items.size());
        assertEquals(4L, item1.getItemID());
        assertEquals(4.3, item1.getValue(), 0.05);
      }
      if (userID == 2L) {
        assertEquals(1, items.size());
        assertEquals(2L, item1.getItemID());
        assertEquals(3.3, item1.getValue(), 0.05);
      }
      if (userID == 3L) {
        assertEquals(2, items.size());
        assertEquals(3L, item1.getItemID());
        assertEquals(4.1, item1.getValue(), 0.05);
        RecommendedItem item2 = items.get(1);
        assertEquals(1L, item2.getItemID());
        assertEquals(3.7, item2.getValue(), 0.05);
      }
      if (userID == 4L) {
        assertEquals(2, items.size());
        assertEquals(2L, item1.getItemID());
        assertEquals(4.0, item1.getValue(), 0.05);
        RecommendedItem item2 = items.get(1);
        assertEquals(3L, item2.getItemID());
        assertEquals(3.5, item2.getValue(), 0.05);
      }
    }
  }
View Full Code Here

TOP

Related Classes of org.apache.mahout.cf.taste.recommender.RecommendedItem

Copyright © 2018 www.massapicom. All rights reserved.
All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.