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Posted to user@predictionio.apache.org by Daniel Gabrieli <dg...@salesforce.com> on 2017/05/14 02:19:00 UTC
UR For New Products
For an e-commerce site, can the UR be used to recommend new products that
have never been purchases?
Re: UR For New Products
Posted by Pat Ferrel <pa...@occamsmachete.com>.
Yes, to all Mars said.
There are several methods so search through the group archives. They amount to:
1) metadata similarity with some example product. So it you are viewing a product similar products can be recommended based on item properties. This is seldom all that useful but you may have really good metadata.
2) popular items narrowed down to the category of the item viewed often preforms better but the recommended items must have some purchases.
3) randomly choose or through some business rules, promote some new items. Then recommend those items based on some promotion category
4) provide a custom ranking of all items, maybe the inverse of the # of days in the catalog, then when no other data exists to make the query these will be returned, newest first.
Any method that returns recs can also use business rules to narrow down what the user sees.
On May 14, 2017, at 6:12 PM, Mars Hall <ma...@heroku.com> wrote:
On May 13, 2017, at 19:19, Daniel Gabrieli <dg...@salesforce.com> wrote:
>
> For an e-commerce site, can the UR be used to recommend new products that have never been purchases?
The Universal Recommender has its own Google group:
https://groups.google.com/forum/?pli=1#!forum/actionml-user
Looks like this question was answered in November:
https://groups.google.com/forum/?pli=1#!searchin/actionml-user/new$20items|sort:relevance/actionml-user/RxPmvdFbWI4/G7YiD-26BgAJ
Sounds like it's possible if item properties are setup correctly during training.
*Mars
( <> .. <> )
Re: UR For New Products
Posted by Mars Hall <ma...@heroku.com>.
On May 13, 2017, at 19:19, Daniel Gabrieli <dg...@salesforce.com> wrote:
>
> For an e-commerce site, can the UR be used to recommend new products that have never been purchases?
The Universal Recommender has its own Google group:
https://groups.google.com/forum/?pli=1#!forum/actionml-user
Looks like this question was answered in November:
https://groups.google.com/forum/?pli=1#!searchin/actionml-user/new$20items|sort:relevance/actionml-user/RxPmvdFbWI4/G7YiD-26BgAJ
Sounds like it's possible if item properties are setup correctly during training.
*Mars
( <> .. <> )