Thank you  @Ted, but my guide is suggesting to go with what Pat is
suggesting. @Pat could you plz tell, if I want to recommend vendors to the
user from the table how they should be grouped and  you mentioned "*your
recs will be returned using the same integer IDs so you will have to
translate your “user1” and “vendor1-service1” into non-negative contiguous
integers*" i don't know about translation could you plz tell more about the
translation.

Thanks and Regards,
Vinayak B


On Tue, Sep 30, 2014 at 10:36 AM, Ted Dunning <[email protected]> wrote:

> Yes.  But I strongly suggest that you not use Pearson Correlation.
>
> Use the LLR similarity to compute indicator actions for each vendor.  Then
> use a user's history of actions to score vendors.  This is not only much
> simpler than what you are asking for, it will be more accurate.
>
> You should also measure additional actions besides ratings.
>
>
>
> On Mon, Sep 29, 2014 at 6:56 PM, vinayakb malagatti <
> [email protected]> wrote:
>
> > @Pat and @Ted Thank You so much for the replay. I was looking for the
> > solution as Pat suggested, here I want to suggest the Vendors to the User
> > which he not yet used by User taking the history of that User and compare
> > with other user who have rated the common vendors. If we take the table
> in
> > that
> >
> >    -   for User 1 - he has rated Vendor 1 ,Vendor 3 and Vendor 4 and
> User 2
> >    has rated Vendor 1, Vendor 2 and Vendor 3.
> >    -  Common between User 2 and User 1 are Vendor 1 and Vendor 3.
> >    - Assume that if Pearson Correlation between them is nearly 1, hence
> we
> >    can Recommend the Vendor 2 to the User 1 which User 1 is not used.
> >
> > Can we do like this, using the Apache Mahout  if Yes could you plz give
> > some brief idea.
> >
> > Thanks and Regards,
> > Vinayak B
> >
> >
> > On Tue, Sep 30, 2014 at 2:10 AM, Ted Dunning <[email protected]>
> > wrote:
> >
> > > I would recommend that you look at actions other than ratings as well.
> > >
> > > Did a user expand and read 1 review?  did they read >3 reviews?
> > >
> > > Did they mark a rating as useful?
> > >
> > > Did they ask for contact information?
> > >
> > > You know your system better than I possibly could, but using other
> > > information in addition to ratings is very important for getting the
> > > highest quality predictive information.
> > >
> > > You can start with ratings, but you should push to get other kinds of
> > > information as much as possible.  Ratings are often given by only a
> very
> > > small number of people.  That severely limits how much value you can
> add
> > > with a recommendation engine.  At the same time most people are busy
> not
> > > giving you ratings, they are doing lots of other things that tell you
> > what
> > > they are thinking and reacting to.  If you don't pay attention to that
> > > additional information, you are handicapping yourself severely.
> > >
> > >
> > > On Mon, Sep 29, 2014 at 9:53 AM, vinayakb malagatti <
> > > [email protected]> wrote:
> > >
> > > > Hi all,
> > > >
> > > > I have table something looks like in DB :
> > > >
> > > >
> > > > ​​​
> > > >  rating table
> > > > <
> > > >
> > >
> >
> https://docs.google.com/spreadsheets/d/1PrShX7X70PqnfIQg0Dfv6mIHtX1k7KSZHTBfTPMv_Do/edit?usp=drive_web
> > > > >
> > > > ​
> > > >
> > > >
> > > >
> > > >
> > > >
> > > > Thanks and Regards,
> > > > Vinayak B
> > > >
> > >
> >
>

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