Good luck. Let us know how it turns out.
On Sun, Sep 11, 2011 at 2:55 PM, Manju <[email protected]> wrote: > Ted and Sean, > Thanks for the suggestion/advice. My prototype ran successfully > (programatically:) with GenericBooleanPrefItemBasedRecommender. I am > reviewing/reflecting on the output. > Thanks again. > Manju > > ------------------------------ > *From:* Ted Dunning <[email protected]> > *To:* [email protected]; Manju <[email protected]> > *Cc:* "[email protected]" <[email protected]> > *Sent:* Sunday, September 11, 2011 3:55 PM > *Subject:* Re: Recommendation with a dataset with no/same preference > > Binary preferences are fine. > > In fact, I generally recommend that all ratings and related information be > distilled down to a single binary indicator such as you already have. > > The fact that you have so few items will be both your advantage and > disadvantage. It will help you avoid problems with sparsity and lack of > overlap between users, but it will also make your life harder because theere > aren't so many items to recommend. This will be exacerbated by your > customers' tendency to exhaustively research items before purchase ... it is > likely that they will know about most related items already. > > On Sun, Sep 11, 2011 at 10:01 AM, Manju <[email protected]> wrote: > > ... have purchase data but not rating data ... > > > > Any advice on how best to approach the scenario with item or user based > recommendation (given the lack of spread in ratings/preferences)? > > > >
