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From 补丁象夫 <>
Subject Re: Feedback on provided recommendations
Date Wed, 28 Apr 2010 04:29:32 GMT
By the way, it's quite a pity that no such dataset is publicly
available with feedbacks on recommendations. As a result, researches
on this topic is quite limited.

2010/4/28, 补丁象夫 <>:
> 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 <>:
>> 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 <> 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.
> --


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