private double doItemSimilarity(long itemID1, long itemID2, long preferring1, long numUsers)
{
DataModel model = base.getDataModel();
long num = model.getNumUsersWithPreferenceFor(itemID1, itemID2);
if (num == 0L)
{
return(double.NaN);
}
long num2 = model.getNumUsersWithPreferenceFor(itemID2);
double num3 = LogLikelihood.logLikelihoodRatio(num, num2 - num, preferring1 - num, ((numUsers - preferring1) - num2) + num);
return(1.0 - (1.0 / (1.0 + num3)));
}
private double doItemSimilarity(long itemID1, long itemID2, long preferring1, long numUsers)
{
IDataModel dataModel = getDataModel();
long preferring1and2 = dataModel.GetNumUsersWithPreferenceFor(itemID1, itemID2);
if (preferring1and2 == 0)
{
return(Double.NaN);
}
long preferring2 = dataModel.GetNumUsersWithPreferenceFor(itemID2);
double logLikelihood =
LogLikelihood.logLikelihoodRatio(preferring1and2,
preferring2 - preferring1and2,
preferring1 - preferring1and2,
numUsers - preferring1 - preferring2 + preferring1and2);
return(1.0 - 1.0 / (1.0 + logLikelihood));
}
public double userSimilarity(long userID1, long userID2)
{
DataModel model = base.getDataModel();
FastIDSet other = model.getItemIDsFromUser(userID1);
FastIDSet set2 = model.getItemIDsFromUser(userID2);
long num = other.size();
long num2 = set2.size();
long num3 = (num < num2) ? ((long)set2.intersectionSize(other)) : ((long)other.intersectionSize(set2));
if (num3 == 0L)
{
return(double.NaN);
}
long num4 = model.getNumItems();
double num5 = LogLikelihood.logLikelihoodRatio(num3, num2 - num3, num - num3, ((num4 - num) - num2) + num3);
return(1.0 - (1.0 / (1.0 + num5)));
}
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));
}