These are slightly different from conventional collaborative filtering, but I think solutions are available.
"Customers with Similar Searches Purchased" To apply user-based CF you need a notion of user-user similarity. You could think of this as a sub-problem, where users are users and searches are items, and apply any of the standard UserSimilarity measures to compute user-user similarity. Then, yes this becomes user-based collaborative filtering, but without ratings. You can just use GenericUserBasedRecommender with your UserSimilarity. That just gets you started -- I think there's room to optimize and improve on that basic start, such as implementing a custom UserNeighborhood. "What Do Customers Ultimately Buy After Viewing This Item" This isn't really CF, but association rule mining. You might look at the "Frequent Pattern Mining" support here instead. On Sun, Aug 29, 2010 at 6:25 PM, Pramit Vamsi <[email protected]> wrote: > Hi, > > I am new to mahout and looking for ideas to implement "Customers with > Similar Searches Purchased" and "What Do Customers Ultimately Buy After > Viewing This Item?" style recommendations on amazon.com. Is it possible with > the current Taste implementation? Any pointers will be helpful. > Thanks, > Pramit >
