Since this is Recommender day, here is another kvetch:
The recommender implementations with algorithms all do this in
Recommender.estimatePreference():
public float estimatePreference(long userID, long itemID) throws
TasteException {
DataModel model = getDataModel();
Float actualPref = model.getPreferenceValue(userID, itemID);
if (actualPref != null) {
return actualPref;
}
return doEstimatePreference(userID, itemID);
}
Meaning: "if I told you something, just parrot it back to me."
Otherwise, make a guess.
I am doing head-to-head comparisons of the dataModel preferences v.s.
the Recommender. This code makes it impossible to directly compare
what the recommender thinks v.s. the actual preference. If I wanted to
know what I told it, I already know that. I want to know what the
recommender thinks.
If this design decision is something y'all have argued about and
settled on, never mind. If it is just something that seemed like a
good idea at the time, can we change the recommenders, and the
Recommender "contract", to always use their own algorithm?
--
Lance Norskog
[email protected]
