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Posted to user@mahout.apache.org by ameh <an...@accenture.com> on 2012/04/05 22:20:58 UTC

Combining CF and Content-based recommendations

Hi, 

I'm a new user to Mahout and am currently using the 1m ratings MovieLens
data file. I had a couple of questions: 

#1. /ItemBased using CF and content-based/
I've been thinking of a way to incorporate content-based recommendations
(using additional attributes of an item, in this case a movie) by utilizing
a utility matrix where the rows correspond to users and columns correspond
to movies. The individual entries (say entry(i,j)) are the preferences
(ratings) expressed by user i for movie j. I know you can include additional
columns, say genre, and identify a value for that entry based on the movies
rated by a particular within that genre type. 

This matrix would be pretty sparse. But I'm not sure *how* to combine this
with the out-of-box recommendations provided in Mahout. How will I do this
if my data model (a matrix) is different from DataModel?

#2. /Adding in demographic information/
I'd like to recommend movies to users, and not users to users, so I'm not
sure how I can incorporate user "attributes" (e.g. their age group,
occupation, etc) without doing this. The Libimseti dating recommendation
makes sense - there, we're recommending users to users. In my case, does it
make sense to just filter based on a particular e.g. age group, and make a
recommendation based on this filtered group? (I guess this rests on the
assumption that my filter will return users that are more similar to each
other because they are in the same demographic category (in this case age
group).) Or is there a better method of doing this?

Any insight or advice based on past experience with this would be very
helpful. Thanks in advance.

--
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Re: Combining CF and Content-based recommendations

Posted by Ahmed Abdeen Hamed <ah...@gmail.com>.
Hi Anita,

I had a similar question to the list not too long ago. I got very good
answers from both Sean and Ted. Please check the archives and if you still
have questions feel free to email me. I am sure I will learn something new.

Good luck!

-Ahmed

On Thu, Apr 5, 2012 at 4:20 PM, ameh <an...@accenture.com> wrote:

> Hi,
>
> I'm a new user to Mahout and am currently using the 1m ratings MovieLens
> data file. I had a couple of questions:
>
> #1. /ItemBased using CF and content-based/
> I've been thinking of a way to incorporate content-based recommendations
> (using additional attributes of an item, in this case a movie) by utilizing
> a utility matrix where the rows correspond to users and columns correspond
> to movies. The individual entries (say entry(i,j)) are the preferences
> (ratings) expressed by user i for movie j. I know you can include
> additional
> columns, say genre, and identify a value for that entry based on the movies
> rated by a particular within that genre type.
>
> This matrix would be pretty sparse. But I'm not sure *how* to combine this
> with the out-of-box recommendations provided in Mahout. How will I do this
> if my data model (a matrix) is different from DataModel?
>
> #2. /Adding in demographic information/
> I'd like to recommend movies to users, and not users to users, so I'm not
> sure how I can incorporate user "attributes" (e.g. their age group,
> occupation, etc) without doing this. The Libimseti dating recommendation
> makes sense - there, we're recommending users to users. In my case, does it
> make sense to just filter based on a particular e.g. age group, and make a
> recommendation based on this filtered group? (I guess this rests on the
> assumption that my filter will return users that are more similar to each
> other because they are in the same demographic category (in this case age
> group).) Or is there a better method of doing this?
>
> Any insight or advice based on past experience with this would be very
> helpful. Thanks in advance.
>
> --
> View this message in context:
> http://lucene.472066.n3.nabble.com/Combining-CF-and-Content-based-recommendations-tp3888524p3888524.html
> Sent from the Mahout User List mailing list archive at Nabble.com.
>