private List <IRecommendedItem> doMostSimilarItems(long[] itemIDs,
int howMany,
TopItems.IEstimator <long> estimator)
{
FastIDSet possibleItemIDs = mostSimilarItemsCandidateItemsStrategy.GetCandidateItems(itemIDs, GetDataModel());
return(TopItems.GetTopItems(howMany, possibleItemIDs.GetEnumerator(), null, estimator));
}
public override IList <IRecommendedItem> Recommend(long userID, int howMany, IDRescorer rescorer)
{
//Preconditions.checkArgument(howMany >= 1, "howMany must be at least 1");
log.Debug("Recommending items for user ID '{}'", userID);
IPreferenceArray preferencesFromUser = GetDataModel().GetPreferencesFromUser(userID);
FastIDSet possibleItemIDs = GetAllOtherItems(userID, preferencesFromUser);
TopItems.IEstimator <long> estimator = new Estimator(this, userID);
List <IRecommendedItem> topItems = TopItems.GetTopItems(howMany, possibleItemIDs.GetEnumerator(), rescorer,
estimator);
log.Debug("Recommendations are: {}", topItems);
return(topItems);
}
public void testTopItems()
{
long[] ids = new long[100];
for (int i = 0; i < 100; i++)
{
ids[i] = i;
}
var possibleItemIds = ((IEnumerable <long>)ids).GetEnumerator();
TopItems.IEstimator <long> estimator = new TestTopItemsEstimator();
List <IRecommendedItem> topItems = TopItems.GetTopItems(10, possibleItemIds, null, estimator);
int gold = 99;
foreach (IRecommendedItem topItem in topItems)
{
Assert.AreEqual(gold, topItem.GetItemID());
Assert.AreEqual(gold--, topItem.GetValue(), 0.01);
}
}
public List <IRecommendedItem> RecommendedBecause(long userID, long itemID, int howMany)
{
//Preconditions.checkArgument(howMany >= 1, "howMany must be at least 1");
IDataModel model = GetDataModel();
TopItems.IEstimator <long> estimator = new RecommendedBecauseEstimator(this, userID, itemID);
IPreferenceArray prefs = model.GetPreferencesFromUser(userID);
int size = prefs.Length();
FastIDSet allUserItems = new FastIDSet(size);
for (int i = 0; i < size; i++)
{
allUserItems.Add(prefs.GetItemID(i));
}
allUserItems.Remove(itemID);
return(TopItems.GetTopItems(howMany, allUserItems.GetEnumerator(), null, estimator));
}
public void testTopItemsRandom()
{
long[] ids = new long[100];
for (int i = 0; i < 100; i++)
{
ids[i] = i;
}
var possibleItemIds = ((IEnumerable <long>)ids).GetEnumerator();
TopItems.IEstimator <long> estimator = new TestRndTopItemsEstimator();
List <IRecommendedItem> topItems = TopItems.GetTopItems(10, possibleItemIds, null, estimator);
Assert.AreEqual(10, topItems.Count);
double last = 2.0;
foreach (IRecommendedItem topItem in topItems)
{
Assert.True(topItem.GetValue() <= last);
last = topItem.GetItemID();
}
}
public override IList <IRecommendedItem> Recommend(long userID, int howMany, IDRescorer rescorer)
{
//Preconditions.checkArgument(howMany >= 1, "howMany must be at least 1");
log.Debug("Recommending items for user ID '{}'", userID);
long[] theNeighborhood = neighborhood.GetUserNeighborhood(userID);
if (theNeighborhood.Length == 0)
{
return(new List <IRecommendedItem>());
}
FastIDSet allItemIDs = getAllOtherItems(theNeighborhood, userID);
TopItems.IEstimator <long> estimator = new Estimator(this, userID, theNeighborhood);
List <IRecommendedItem> topItems = TopItems
.GetTopItems(howMany, allItemIDs.GetEnumerator(), rescorer, estimator);
log.Debug("Recommendations are: {}", topItems);
return(topItems);
}