Okay, sounds a bit clearer. When I look at the docs: http://actionml.com/docs/ur_input, it's still not that clear how the data is send to the eventserver for training.
"Each cart would have a “user-id” or unique identifier per cart" In my case, this is the transaction id (cart, user-id in the json) with the item ids that belong to the transaction as property? Or can the TargetEntityType take an array? 2017-05-16 23:01 GMT+02:00 Pat Ferrel <[email protected]>: > If you want “things that belong in this same shopping cart” you need to > train a model on shopping carts. Each cart would have a “user-id” or unique > identifier per cart (nor really a user-id but that is how it would be > input), then you would request item-set recommendations for the current > contents of the shopping cart. > > If you make the same query after training on user events like “purchase” > you will get similar items. This may give you items that look a lot like > what you have in the cart already and not be what you want. You want things > that go with the cart contents not things like the cart contents. > > In this sense the template you were using before is incorrect, you should > have used “complimentary purchases". But no worry the UR does both (and > others), you just need to input different event encodings to get the 2 > different results. > > > > On May 16, 2017, at 12:50 PM, Dennis Honders <[email protected]> > wrote: > > My intent was not to mix the user id and item ids but maybe show a list > of recommendations by the user id and another list by the item ids. > The current use case is shopping cart recommendations. So I both have a > user id and a list of item ids in the shopping cart. > > 2017-05-16 19:42 GMT+02:00 Pat Ferrel <[email protected]>: > >> Answers below: >> >> >> On May 16, 2017, at 10:19 AM, Dennis Honders <[email protected]> >> wrote: >> >> Hi, >> >> 1. >> I already used similar product template for experimenting. >> https://predictionio.incubator.apache.org/templates/ >> similarproduct/quickstart/ >> >> For UR, are the data queries for the eventserver about the same, but can >> take more properties? In my case three events. Set users, set items and set >> buys. >> >> The UR only needs the buys and determines users and items from the buys, >> you’d do better is you have other events like product detail views, or >> category of item bought, etc. >> >> 2. >> I have coordinates for the users. Is this supported as property? >> >> Yes to location but lat/lon is problematic. Some area location like >> postal code or something like country+province+city works much better. >> These need to be able to contain more than one person so lat/lon is >> theoretically not applicable since it is too fine grained. >> >> Note: in my case I like to make predictions by user id and by an array of >> item ids which is supported, also for products that are never bought for >> cold start. I have item properties like category id, manufacturer id, label >> and price range. >> >> All are supported but I’ll warn that you should test these results, >> mixing user-id and item-sets has no theoretical basis for working and >> without correct boosting of one over the other may interfere and create >> less good results. Also item-sets can work to produce either "similar >> items" or “complimentary items” as in things you might want in the same >> shopping cart. These require different model building. >> >> How are you generating the array of items? what is your goal for this? If >> you want items similar to the one being viewed—on the current page for >> instance, use an item-based query, it will return similar items to the one >> viewed and can mix with user-based items. >> >> In general everything you mention is supported but my gut feel is that it >> may be overly complicated so I’d advise A/B testing with a stripped down >> simple query against this query to see if it really does produce better >> conversions. Let you data be your guide—intuition must be tested. Adding >> rules is often needed and is supported but may also reduce conversion lift >> in unexpected ways. >> >> Thanks in advance >> >> > >
