How are you using LLR to compute user similarity? It is normally used to
compute item similarity?
Also, what is your scale? how many users? how many items? how many
actions per user?
On Mon, Sep 29, 2014 at 6:24 PM, Parimi Rohit
wrote:
> Hi,
>
> I am exploring a random-walk based algorithm
Ted, Thanks for your response. Following is the information about the
approach and the datasets:
I am using the ItemSimilarityJob and passing it "itemID, userID,
prefCount" tuples as input to compute user-user similarity using LLR. I
read this approach from a response for one of the stackoverflow
This is an incredibly tiny dataset. If you delete singletons, it is likely
to get significantly smaller.
I think that something like LDA might work much better for you. It was
designed to work on small data like this.
On Tue, Sep 30, 2014 at 11:13 AM, Parimi Rohit
wrote:
> Ted, Thanks for you
Ted,
I know LDA can be used to model text data but never used it in this
setting. Can you please give me some pointers on how I can apply it in this
setting?
Thanks,
Rohit
On Tue, Sep 30, 2014 at 4:33 PM, Ted Dunning wrote:
> This is an incredibly tiny dataset. If you delete singletons, it is
Here is a paper that includes an analysis of voting patterns using LDA.
http://arxiv.org/pdf/math/0604410.pdf
On Tue, Sep 30, 2014 at 7:04 PM, Parimi Rohit
wrote:
> Ted,
>
> I know LDA can be used to model text data but never used it in this
> setting. Can you please give me some pointers on
Thanks Ted! Will look into it.
Rohit
On Wed, Oct 1, 2014 at 1:04 AM, Ted Dunning wrote:
> Here is a paper that includes an analysis of voting patterns using LDA.
>
> http://arxiv.org/pdf/math/0604410.pdf
>
>
>
> On Tue, Sep 30, 2014 at 7:04 PM, Parimi Rohit
> wrote:
>
> > Ted,
> >
> > I know L
