public static List <IRecommendedItem> GetTopItems(int howMany,
IEnumerator <long> possibleItemIDs,
IDRescorer rescorer,
IEstimator <long> estimator)
{
//Preconditions.checkArgument(possibleItemIDs != null, "possibleItemIDs is null");
//Preconditions.checkArgument(estimator != null, "estimator is null");
var topItems = new SortedSet <IRecommendedItem>(ByValueRecommendedItemComparator.getReverseInstance());
bool full = false;
double lowestTopValue = Double.NegativeInfinity;
while (possibleItemIDs.MoveNext())
{
long itemID = possibleItemIDs.Current;
if (rescorer == null || !rescorer.isFiltered(itemID))
{
double preference;
try {
preference = estimator.Estimate(itemID);
} catch (NoSuchItemException nsie) {
continue;
}
double rescoredPref = rescorer == null ? preference : rescorer.rescore(itemID, preference);
if (!Double.IsNaN(rescoredPref) && (!full || rescoredPref > lowestTopValue))
{
topItems.Add(new GenericRecommendedItem(itemID, (float)rescoredPref));
if (full)
{
topItems.Remove(topItems.Min);
}
else if (topItems.Count > howMany)
{
full = true;
topItems.Remove(topItems.Min); // topItems.poll();
}
lowestTopValue = topItems.Min.GetValue();
}
}
}
int size = topItems.Count;
if (size == 0)
{
return(new List <IRecommendedItem>());
}
List <IRecommendedItem> result = new List <IRecommendedItem>(size);
result.AddRange(topItems);
result.Reverse();
//Collections.sort(result, ByValueRecommendedItemComparator.getInstance());
return(result);
}
public static List <RecommendedItem> getTopItems(int howMany, IEnumerator <long> possibleItemIDs, IDRescorer rescorer, Estimator <long> estimator)
{
SortedSet <RecommendedItem> collection = new SortedSet <RecommendedItem>(ByValueRecommendedItemComparator.getReverseInstance());
bool flag = false;
double negativeInfinity = double.NegativeInfinity;
while (possibleItemIDs.MoveNext())
{
long current = possibleItemIDs.Current;
if ((rescorer == null) || !rescorer.isFiltered(current))
{
double num3;
try
{
num3 = estimator.estimate(current);
}
catch (NoSuchItemException)
{
continue;
}
double d = (rescorer == null) ? num3 : rescorer.rescore(current, num3);
if (!double.IsNaN(d) && (!flag || (d > negativeInfinity)))
{
collection.Add(new GenericRecommendedItem(current, (float)d));
if (flag)
{
collection.Remove(collection.Min);
}
else if (collection.Count > howMany)
{
flag = true;
collection.Remove(collection.Min);
}
negativeInfinity = collection.Min.getValue();
}
}
}
int count = collection.Count;
if (count == 0)
{
return(new List <RecommendedItem>());
}
List <RecommendedItem> list = new List <RecommendedItem>(count);
list.AddRange(collection);
list.Reverse();
return(list);
}
public static long[] GetTopUsers(int howMany,
IEnumerator <long> allUserIDs,
IDRescorer rescorer,
IEstimator <long> estimator)
{
var topUsers = new SortedSet <SimilarUser>();
bool full = false;
double lowestTopValue = Double.NegativeInfinity;
while (allUserIDs.MoveNext())
{
long userID = allUserIDs.Current;
if (rescorer != null && rescorer.isFiltered(userID))
{
continue;
}
double similarity;
try {
similarity = estimator.Estimate(userID);
} catch (NoSuchUserException nsue) {
continue;
}
double rescoredSimilarity = rescorer == null ? similarity : rescorer.rescore(userID, similarity);
if (!Double.IsNaN(rescoredSimilarity) && (!full || rescoredSimilarity > lowestTopValue))
{
topUsers.Add(new SimilarUser(userID, rescoredSimilarity));
if (full)
{
topUsers.Remove(topUsers.Max); // topUsers.poll();
}
else if (topUsers.Count > howMany)
{
full = true;
topUsers.Remove(topUsers.Max); // topUsers.poll();
}
lowestTopValue = topUsers.Max.getSimilarity();
}
}
int size = topUsers.Count;
if (size == 0)
{
return(NO_IDS);
}
List <SimilarUser> sorted = new List <SimilarUser>(size);
return(topUsers.Select(s => s.getUserID()).ToArray());
}
public static long[] getTopUsers(int howMany, IEnumerator <long> allUserIDs, IDRescorer rescorer, Estimator <long> estimator)
{
SortedSet <SimilarUser> set = new SortedSet <SimilarUser>();
bool flag = false;
double negativeInfinity = double.NegativeInfinity;
while (allUserIDs.MoveNext())
{
long current = allUserIDs.Current;
if ((rescorer == null) || !rescorer.isFiltered(current))
{
double num3;
try
{
num3 = estimator.estimate(current);
}
catch (NoSuchUserException)
{
continue;
}
double d = (rescorer == null) ? num3 : rescorer.rescore(current, num3);
if (!double.IsNaN(d) && (!flag || (d > negativeInfinity)))
{
set.Add(new SimilarUser(current, d));
if (flag)
{
set.Remove(set.Max);
}
else if (set.Count > howMany)
{
flag = true;
set.Remove(set.Max);
}
negativeInfinity = set.Max.getSimilarity();
}
}
}
int count = set.Count;
if (count == 0)
{
return(NO_IDS);
}
List <SimilarUser> list = new List <SimilarUser>(count);
return((from s in set select s.getUserID()).ToArray <long>());
}
public override List <RecommendedItem> recommend(long userID, int howMany, IDRescorer rescorer)
{
// Preconditions.checkArgument(howMany >= 1, "howMany must be at least 1");
if (howMany < 1)
{
throw new Exception("howMany must be at least 1");
}
;
buildClusters();
log.debug("Recommending items for user ID '{}'", userID);
List <RecommendedItem> recommended = topRecsByUserID.get(userID);
if (recommended == null)
{
return(new List <RecommendedItem>());
}
DataModel dataModel = getDataModel();
List <RecommendedItem> rescored = new List <RecommendedItem>(); //Lists.newArrayListWithCapacity(recommended.size());
// Only add items the user doesn't already have a preference for.
// And that the rescorer doesn't "reject".
foreach (RecommendedItem recommendedItem in recommended)
{
long itemID = recommendedItem.getItemID();
if (rescorer != null && rescorer.isFiltered(itemID))
{
continue;
}
if (dataModel.getPreferenceValue(userID, itemID) == null &&
(rescorer == null || !Double.IsNaN(rescorer.rescore(itemID, recommendedItem.getValue()))))
{
rescored.Add(recommendedItem);
}
}
rescored.Sort(new ByRescoreComparator(rescorer));
return(rescored);
}