public double UserSimilarity(long userID1, long userID2)
{
IDataModel dataModel = getDataModel();
FastIDSet xPrefs = dataModel.GetItemIDsFromUser(userID1);
FastIDSet yPrefs = dataModel.GetItemIDsFromUser(userID2);
int xPrefsSize = xPrefs.Count();
int yPrefsSize = yPrefs.Count();
if (xPrefsSize == 0 && yPrefsSize == 0)
{
return(Double.NaN);
}
if (xPrefsSize == 0 || yPrefsSize == 0)
{
return(0.0);
}
int intersectionSize =
xPrefsSize < yPrefsSize?yPrefs.IntersectionSize(xPrefs) : xPrefs.IntersectionSize(yPrefs);
if (intersectionSize == 0)
{
return(Double.NaN);
}
int unionSize = xPrefsSize + yPrefsSize - intersectionSize;
return((double)intersectionSize / (double)unionSize);
}
public double UserSimilarity(long userID1, long userID2)
{
IDataModel dataModel = getDataModel();
FastIDSet prefs1 = dataModel.GetItemIDsFromUser(userID1);
FastIDSet prefs2 = dataModel.GetItemIDsFromUser(userID2);
int prefs1Size = prefs1.Count();
int prefs2Size = prefs2.Count();
int intersectionSize = prefs1Size < prefs2Size?prefs2.IntersectionSize(prefs1) : prefs1.IntersectionSize(prefs2);
return(doSimilarity(prefs1Size, prefs2Size, intersectionSize));
}
public override int GetNumUsersWithPreferenceFor(long itemID1, long itemID2)
{
FastIDSet userIDs1 = preferenceForItems.Get(itemID1);
if (userIDs1 == null)
{
return(0);
}
FastIDSet userIDs2 = preferenceForItems.Get(itemID2);
if (userIDs2 == null)
{
return(0);
}
return(userIDs1.Count() < userIDs2.Count()
? userIDs2.IntersectionSize(userIDs1)
: userIDs1.IntersectionSize(userIDs2));
}
public double UserSimilarity(long userID1, long userID2)
{
IDataModel dataModel = getDataModel();
FastIDSet prefs1 = dataModel.GetItemIDsFromUser(userID1);
FastIDSet prefs2 = dataModel.GetItemIDsFromUser(userID2);
long prefs1Size = prefs1.Count();
long prefs2Size = prefs2.Count();
long intersectionSize =
prefs1Size < prefs2Size?prefs2.IntersectionSize(prefs1) : prefs1.IntersectionSize(prefs2);
if (intersectionSize == 0)
{
return(Double.NaN);
}
long numItems = dataModel.GetNumItems();
double logLikelihood =
LogLikelihood.logLikelihoodRatio(intersectionSize,
prefs2Size - intersectionSize,
prefs1Size - intersectionSize,
numItems - prefs1Size - prefs2Size + intersectionSize);
return(1.0 - 1.0 / (1.0 + logLikelihood));
}