You have two sources of information, feedbacks on recommendations and ratings volunteerly provided by the users. Therefore, the model should balance those two types of information.
As to how to utilize the feedbacks on recommendations, I think it's a learning-to-rank task. Recommended items with negative feedbacks should not be taken as irrelevant items, they are only less relevant compared with recommendations with positive feedbacks or no feedbacks. There are many works on learning to rank, and CofiRank by Yahoo is probably the first work to adopt such method for collaborative filtering. 2010/4/28, Sean Owen <sro...@gmail.com>: > You are talking about feedback on recommendations, right? When a user > says "that recommendation you presented to me is not a good > recommendation"? I think this is fairly different information from a > user volunteering that "I don't like that item." An item that a user > rates poorly is still, strangely, an item that is relevant to that > user. > > I kind of wrote about this in the book -- let's say you are a > hard-core classical music fan. You love Brahms (5 stars) but can't > stand the showy Vivaldi (1 star). If I recommended Led Zeppelin to > you, you would undoubtedly say it's a bad recommendation. But it is > 'bad' in a different way that Vivaldi is bad. Vivaldi is something you > knew about already because it was similar to things you do like -- Led > Zeppelin was completely foreign and unrelated. > > Negative ratings like the 1 star that the user volunteered for > Vivaldi, therefore, mean some different and should be treated > differently than the user's response to the Led Zeppelin > recommendation that was pushed at him or her. > > > I would agree with Ted, that negative feedback on recommendations > doesn't somehow belong in the data model. You can use it to filter > recommendations -- you would want to purge any Led Zeppelin records > from recommendations going forward. In the (non-distributed) > framework, this is done with a Rescorer. > > That is, you don't need to or want to add this negative feedback into > the model. There's no problem of boolean ratings and such since the > association would not exist in the model -- just in recommendation > filters. > > > > On Tue, Apr 27, 2010 at 6:27 PM, Tolga Oral <tolga.o...@gmail.com> wrote: >> We are building a system on top of provided recommendations allowing user >> to >> provide feedback. I have a question on how to apply the negative feedback >> for both boolean and none boolean scores. >> >> Assuming its a boolean item (item with no score), I cant see how we can >> provide negative feedback for a given recommendation. Does this mean we >> should convert our boolean items to a score of 1 and give score of -1 (or >> 0) >> for recommendations that user didnt like? >> >> This applies to items with score too I am not sure if the correct way of >> going about this is to provide 0 or a negative value. >> >> Thank you. >> > -- http://blog.sina.com.cn/apachemahout
