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

Examples of org.apache.mahout.cf.taste.impl.common.FastIDSet.addAll()

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        }
      }
     
      // Make new merged cluster
      FastIDSet merged = new FastIDSet(cluster1.size() + cluster2.size());
      merged.addAll(cluster1);
      merged.addAll(cluster2);
     
      // Compare against other clusters; update queue if needed
      // That new pair we're just adding might be pretty close to something else, so
      // catch that case here and put it back into our queue
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      }
     
      // Make new merged cluster
      FastIDSet merged = new FastIDSet(cluster1.size() + cluster2.size());
      merged.addAll(cluster1);
      merged.addAll(cluster2);
     
      // Compare against other clusters; update queue if needed
      // That new pair we're just adding might be pretty close to something else, so
      // catch that case here and put it back into our queue
      for (FastIDSet cluster : clusters) {
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    DataModel dataModel = getDataModel();
    FastIDSet possibleItemIDs = new FastIDSet();
    LongPrimitiveIterator it = cluster.iterator();
    while (it.hasNext()) {
      possibleItemIDs.addAll(dataModel.getItemIDsFromUser(it.next()));
    }
   
    TopItems.Estimator<Long> estimator = new Estimator(cluster);
   
    List<RecommendedItem> topItems = TopItems.getTopItems(NUM_CLUSTER_RECS,
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    FastIDSet possibleItemsIDs = new FastIDSet();
    for (long itemID : preferredItemIDs) {
      PreferenceArray itemPreferences = dataModel.getPreferencesForItem(itemID);
      int numUsersPreferringItem = itemPreferences.length();
      for (int index = 0; index < numUsersPreferringItem; index++) {
        possibleItemsIDs.addAll(dataModel.getItemIDsFromUser(itemPreferences.getUserID(index)));
      }
    }
    possibleItemsIDs.removeAll(preferredItemIDs);
    return possibleItemsIDs;
  }
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        }
      }
     
      // Make new merged cluster
      FastIDSet merged = new FastIDSet(cluster1.size() + cluster2.size());
      merged.addAll(cluster1);
      merged.addAll(cluster2);
     
      // Compare against other clusters; update queue if needed
      // That new pair we're just adding might be pretty close to something else, so
      // catch that case here and put it back into our queue
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      }
     
      // Make new merged cluster
      FastIDSet merged = new FastIDSet(cluster1.size() + cluster2.size());
      merged.addAll(cluster1);
      merged.addAll(cluster2);
     
      // Compare against other clusters; update queue if needed
      // That new pair we're just adding might be pretty close to something else, so
      // catch that case here and put it back into our queue
      for (FastIDSet cluster : clusters) {
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    DataModel dataModel = getDataModel();
    FastIDSet possibleItemIDs = new FastIDSet();
    LongPrimitiveIterator it = cluster.iterator();
    while (it.hasNext()) {
      possibleItemIDs.addAll(dataModel.getItemIDsFromUser(it.nextLong()));
    }
   
    TopItems.Estimator<Long> estimator = new Estimator(cluster);
   
    List<RecommendedItem> topItems = TopItems.getTopItems(NUM_CLUSTER_RECS,
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  @Override
  protected FastIDSet getAllOtherItems(long[] theNeighborhood, long theUserID) throws TasteException {
    DataModel dataModel = getDataModel();
    FastIDSet possibleItemIDs = new FastIDSet();
    for (long userID : theNeighborhood) {
      possibleItemIDs.addAll(dataModel.getItemIDsFromUser(userID));
    }
    possibleItemIDs.removeAll(dataModel.getItemIDsFromUser(theUserID));
    return possibleItemIDs;
  }
 
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  protected FastIDSet getAllOtherItems(long[] theNeighborhood, long theUserID) throws TasteException {
    DataModel dataModel = getDataModel();
    FastIDSet possibleItemIDs = new FastIDSet();
    for (long userID : theNeighborhood) {
      possibleItemIDs.addAll(dataModel.getItemIDsFromUser(userID));
    }
    possibleItemIDs.removeAll(dataModel.getItemIDsFromUser(theUserID));
    return possibleItemIDs;
  }
 
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  @Override
  FastIDSet doGetCandidateItems(long[] preferredItemIDs, DataModel dataModel) throws TasteException {
    FastIDSet candidateItemIDs = new FastIDSet();
    for (long itemID : preferredItemIDs) {
      candidateItemIDs.addAll(similarity.allSimilarItemIDs(itemID));
    }
    candidateItemIDs.removeAll(preferredItemIDs);
    return candidateItemIDs;
  }
}
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