Yeah, though that's not recommend(), that's estimatePreference(). It could throw an exception or something but seemed nicer to return the answer it has; this isn't an intended use case.
If you include known data in the test, it's going to get the estimate exactly right, and that doesn't say anything about the recommender, so known data is not sent to this method in a test anyway. On Sat, Jan 28, 2012 at 10:06 PM, Lance Norskog <[email protected]> wrote: > > I think it would be surprising behavior for a recommender to return data > it > already knows; I just think the implicit contract is to return only > predictions. That's how real-world recommender systems appear to behave, to > the end user; Amazon doesn't show you books you have already read, even if > indeed they may be some of your favorites ever. > > The current recommender algorithms do this. > SlopeOneRecommender: estimatePreference(), line 123: > 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); > } > > As do all of the other recommenders, where the algorithm makes it > possible. This makes <1% difference in the RMSE. > > On Sat, Jan 28, 2012 at 12:33 PM, Ted Dunning <[email protected]> > wrote: > > Also, Lee, I think you have it backwards. It is true that clicks are not > > the same thing as preferences, but I don't think that I give a fig about > > preferences since they are the internal mental state of the visitor. I > > know that some of the visitors are mental, but I don't really care since > > that is their own business. What I care about is encouraging certain > > behaviors. > > > > So I find that mental state estimations are the indirect way to model and > > predict behaviors while directly modeling behaviors based on observed > > behaviors is, well, more direct. > > > > This is compounded by the fact that asking people to rate things invokes > a > > really complicated social interaction which does not directly sample the > > internal mental state (i.e. the real preference) but instead measures > > behavior that is a very complicated outcome of social pressures, > > expectations and the internal mental state. So using ratings boils down > to > > using one kind of behavior to estimate mental state that then is > > hypothesized to result in the desired second kind of behavior. > > > > > > > > On Sat, Jan 28, 2012 at 10:51 AM, Sean Owen <[email protected]> wrote: > > > >> It means *something* that a user clicked on one item and not 10,000 > others. > >> You will learn things like that Star Wars and Star Trek are somehow > related > >> from this data. I don't think that clicks are a bad input per se. > >> > >> I agree that it's not obvious how to meaningfully translate user actions > >> into a linear scale. "1" per click and "10" for purchase or something > is a > >> guess. I do think you will learn something from the data this way. > >> > >> There is nothing conceptually wrong with mixing real data and estimated > >> data. If the results aren't looking right, it is not a problem with the > >> concept, but the mapping of action onto some rating scale. I think it's > >> hard to get that right, but is not impossible to get it "good". > >> > >> On Sat, Jan 28, 2012 at 10:15 AM, Lee Carroll > >> <[email protected]>wrote: > >> > >> > > I would argue, though, that .recommend() is aimed at the latter > task: > >> > > >> > No . I think the mismatch here is you are using at best a wild guess > >> > at a preference for the convenience of using a recommender and then in > >> > the same breath expecting the recommender to "understand" that you are > >> > not using preferences at all and actually have no idea what the user > >> > preference is. You cant have it both ways :-) > >> > > >> > A click through on an item is not a measure of user preference for > >> > that item. I know its not what you want to hear (or better what your > >> > business users want to here) but there it is. > >> > > >> > We can pretend, or maybe even build a convincing narrative that a > >> > click is some sort of item association and use that as a proxy > >> > preference and we might even get some mileage out of it, but we should > >> > not change the behaviour of the .recommend() to hide its short > >> > comings. > >> > > >> > > > > -- > Lance Norskog > [email protected] >
