
Recommender Systems for Social Bookmarking (2009 Ph.D. thesis) - jashmenn
http://ilk.uvt.nl/~toine/phd-thesis/
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sidmitra
I was just discussing about recommendation engines with a friend yesterday.

My pet peeve is that i find a lot of the companies,datasets,research focus on
the positive aspects of recommendation. There is probably a lot more negative
data we're missing out on, which is not being collected a lot. That data
consists of things i would "hate". I would want to chart out a hate pattern of
the internet and an anti-pagerank of sorts.

I was reading a post about the same thing yesterday(1), linked along with some
questions of my own at <http://blog.sidmitra.com/where-is-my-dislike-button>.

Ref: [http://blog.superfeedr.com/social/algorithm/a-social-
filteri...](http://blog.superfeedr.com/social/algorithm/a-social-filtering-
algorithm/)

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nkurz
Good point. Beyond the usual 'people who like this also like', there are some
interesting inversions:

    
    
      1) People who hate this also hate
      2) People who hate this also like
      3) People who like this also hate
    

Judicious use of these might help to provide the serendipity you mention in
the linked post.

But in practice, I think there are a number of reasons that you don't see
'dislike' buttons as frequently.

    
    
      1) The common KNN item-item approach doesn't handle negative correlations. 
      2) Without explicit ratings, dislike is harder to infer than like.
      3) Sites just don't like appearing to be negative.

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jacabado
1) Space for algorithmic innovation? (which is the coolest thing to be in
front of but I guess there must be already some algorithm application to
handle this case) 2) Why? Could you give some examples? I ask because I also
think that rating-less like is dependent on the subjects personality. For me a
dislike button should be much more meaningful because as a optimistic there is
a bigger range of things I like with a bigger variation of likeness, while
when I (would) hit dislike I must be pretty sure that I don't like it. 3) I
agree but the implication is that sites should use negative qualifications
differently, it shouldn't be shared with others in the same way the likeness
is shared unless, as in your suggestions, they enable you to find better
content. I don't go telling people I dislike that I dislike them, I just avoid
them. The approach should be similar.

~~~
nkurz
Personally, I think there is a lot of room for algorithmic improvement on
recommendations. Most of the existing systems are really prediction
algorithms, which have been shoe-horned into making recommendations. I think
this is primarily because accuracy of prediction is easier to measure (RMSE)
than accuracy of recommendation, and the academic papers need something they
can measure.

I agree that inferring 'like' is also difficult, and definitely prefer
explicit rating systems. But for a site like Amazon, it's often a reasonable
presumption that a user who buys an item likes it. But inferring that they
dislike all the items they don't purchase is much less reasonable. Same for
viewing webpages, or listening to music, or renting movies. If you want to be
sure of a 'dislike', it probably will require action from the user.

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joshu
The main issue I had building or of these for delicious was not the algorithm
(many techniques yielded pleasing results) but instead scaling to get any
reasonable performance.

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wslh
This obsession with recommendation systems! the thing is when you like a lot
of things that algorithms can't tell (or better: there is not enough
information to train those algorithms).

