The existence of a rating, no matter what it is, generates an
emotional engagement. "2.7? What idiots hate this? The kitten is a
genius!".
When I was involved in such a system, I wanted to randomly generate
ratings. There is no SLA in a consumer site where you watch videos for
free. You might get
I bet the name becomes very appropriate very quickly.
The other category of repeated viewing is click-spamming. They are very
much worth ignoring as well.
In any case, I have found that it is very important to almost entirely
ignore the number of times that somebody interacts with a media item (
On May 20, 2011, at 10:11 PM, Ted Dunning wrote:
> Also, from a practical point of view, people rarely watch videos repeatedly,
> even if they like them and want to see more.
>
> (people - excluding two year olds who will watch something they like until
> it wears out)
I would extend that from
For using Mahout in production you need a feedback loop. The
implementers are drawn to sexy things like great algorithms, and can
print out a bunch of numbers and say, "ok, that looks right". I keep
hacking up ways to interpret and view what Mahout spits out, and I'm
not happy with any of them.
On
Also, from a practical point of view, people rarely watch videos repeatedly,
even if they like them and want to see more.
(people - excluding two year olds who will watch something they like until
it wears out)
On Fri, May 20, 2011 at 7:04 PM, Sean Owen wrote:
> I agree that ratings contain rel
I agree that ratings contain relatively little data. Here you're not using
direct ratings, but inferring some notion of rating from impressions. Does
your scheme make sense? It's not illogical but not one I would choose. To
me, there is the most "information" in the jump from 0 impressions to 1.
Th
I published an article in my blog at http://ssc.io recently that deals with
scaling recommender systems, i'm sure it has some ideas you could adapt.
--sebastian
Am 20.05.2011 20:02 schrieb "Ted Dunning" :
> Sean will be able to address scaling and configuration better than I, but
I
> have built vi
Sean will be able to address scaling and configuration better than I, but I
have built video recommendation systems before and found that
a) ratings are nearly worthless, largely because so few people will rate
things
b) the best preference data we ever found was whether the user viewed the
asset
Hi,
I have been considering using mahout for our recommendation engine
needs and had couple of questions about using it in production.
Use Case:
We need to provide recommendation on video assets (similar to hulu) to
couple of million users and we have over 100K assets. Since we are
experiencing gr
