1
$\begingroup$

I'm trying to build recommender based on user history from e-commerce. There are two(potentially more) types of events: purchase and view. Is it okay to sum up number of purchases and views for a given item(with purchase and view having different weights)? Or I`ll just mix up user intent this way?

$\endgroup$
1
$\begingroup$

I assume you're using an implicit feedback recommender approach like ALS. Otherwise, summing data points generally won't make sense, such as if you're feeding it to a recommender that expects ratings.

The input to implicit ALS is, conceptually, weighted user-item pairs. Therefore it makes sense to perhaps use a sum of user-item clicks as the weight. Summing makes sense.

However, does a purchase and view seem to carry the same weight? obviously not. A purchase is a much stronger association and should be weighted accordingly.

As to how much, I'd suggest weighting purchases simply by price, to start. Then weight clicks by price times purchase-to-click ratio. A $10 item purchase is weight 10; if 1 in 200 clicks results in a purchase, then weight a click 0.2.

This is crude but probably about as close as anything for capturing this info in the context of ALS.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.