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

Examples of org.apache.mahout.cf.taste.impl.recommender.CachingRecommender$Recommendations

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  }

  public void testItemLoad() throws Exception {
    DataModel model = createModel();
    ItemSimilarity itemSimilarity = new PearsonCorrelationSimilarity(model);
    Recommender recommender = new CachingRecommender(new GenericItemBasedRecommender(model, itemSimilarity));
    doTestLoad(recommender, 240);
  }
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  public void testUserLoad() throws Exception {
    DataModel model = createModel();
    UserSimilarity userSimilarity = new PearsonCorrelationSimilarity(model);
    UserNeighborhood neighborhood = new NearestNUserNeighborhood(10, userSimilarity, model);
    Recommender recommender =
            new CachingRecommender(new GenericUserBasedRecommender(model, neighborhood, userSimilarity));
    doTestLoad(recommender, 40);
  }
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public final class JesterRecommender implements Recommender {
 
  private final Recommender recommender;
 
  public JesterRecommender(DataModel dataModel) throws TasteException {
    recommender = new CachingRecommender(new SlopeOneRecommender(dataModel));
  }
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   *
   * @param dataModel data model
   * @throws TasteException if an error occurs while initializing this
   */
  public GroupLensRecommender(DataModel dataModel) throws TasteException {
    recommender = new CachingRecommender(new SlopeOneRecommender(dataModel));
  }
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   *
   * @param dataModel data model
   * @throws TasteException if an error occurs while initializing this {@link GroupLensRecommender}
   */
  public GroupLensRecommender(DataModel dataModel) throws TasteException {
    recommender = new CachingRecommender(new SlopeOneRecommender(dataModel));
  }
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  private final Recommender recommender;

  public BookCrossingRecommender(DataModel bcModel) throws TasteException {
    UserSimilarity similarity = new PearsonCorrelationSimilarity(bcModel);
    UserNeighborhood neighborhood = new NearestNUserNeighborhood(10, 0.0, similarity, bcModel, 0.1);
    recommender = new CachingRecommender(new GenericUserBasedRecommender(bcModel, neighborhood, similarity));
  }
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public final class JesterRecommender implements Recommender {

  private final Recommender recommender;

  public JesterRecommender(DataModel dataModel) throws TasteException {
    recommender = new CachingRecommender(new SlopeOneRecommender(dataModel));
  }
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            100, similarity, model);

    Recommender recommender =  new GenericUserBasedRecommender(
        model, neighborhood, similarity);

    Recommender cachingRecommender = new CachingRecommender(recommender);

    for(int userId: userIds) {
      System.out.println("UserID " + userId);
      List<RecommendedItem> recommendations =
          cachingRecommender.recommend(userId, 2);
      for(RecommendedItem item: recommendations) {
        System.out.println("  item " + item.getItemID() + " score " + item.getValue());
      }
    }
  }
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Related Classes of org.apache.mahout.cf.taste.impl.recommender.CachingRecommender$Recommendations

  • com.manning.hip.ch9.MovieUserRecommender
  • org.apache.mahout.cf.taste.example.bookcrossing.BookCrossingRecommender
  • org.apache.mahout.cf.taste.example.grouplens.GroupLensRecommender
  • org.apache.mahout.cf.taste.example.jester.JesterRecommender
  • org.apache.mahout.cf.taste.impl.common.RefreshHelper
  • org.apache.mahout.cf.taste.impl.LoadTest
  • org.apache.mahout.cf.taste.recommender.IDRescorer
  • org.apache.mahout.common.LongPair
  • java.util.concurrent.atomic.AtomicInteger
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