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Creating schema with type "null" for genres throws error on AWS Console for Amazon Personalize
Using a web console for Amazon Personalize for creating item datasets, it throws an error "GENRES field cannot be of type null" when trying to create an item schema with GENRES that contains type "null".
But the documentation https://docs.aws.amazon.com/personalize/latest/dg/how-it-works-dataset-schema.html has GENRES with type null for imperfect data.
Also, it throws an error "schema is missing required field [genres]" if it's not included in the schema, which is odd, because the documentation says that the item schema requires ITEM_ID, CREATION_TIMESTAMP, and 1 metadata field where the table doesn't even mention genres. https://docs.aws.amazon.com/personalize/latest/dg/custom-datasets-and-schemas.html#dataset-requirements
However, we could create the schema without genres when using the AWS SDK. Is this a bug in AWS console? or is it a new requirement that hasn't been updated on SDK?
Accepted AnswerAmazon Personalize
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asked 11 days ago
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asked 8 months ago
How to delete recorded events for user-interactions dataset ?
I have been trying to delete the user-item interactions dataset, but the data imported with putevents(recorded events with event tracker) still remain, only bulk data gets deleted
Any solutions?
Accepted AnswerAmazon Personalize
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asked 9 months ago
How to get a new solution version using only recent records?
How to generate a solution version(USER_PERSONALIZATION recipes) using only recent records when importing records incrementally?
I’m importing records(interactions, items) incrementally since new items are created every time.
Since importing records incrementally makes training time(price) very high and the integrated records contains unnecessary old items, I want to generate a new solution version using only recent records(interaction, items). Is there any ways to do this?
As far as i know, there is no way to remove old records when generating a new solution version.
Currently, i’m generating a new solution version on all items(old and new) and remove the old items using filter when recommending items.
**Q1. If I want to get a new solution version using only recent records, Do I have to create a new DatasetGroup?**
**Q2. If new items are created every time and old items are unnecessary(e.g. news article recommendations), what is a proper personalize architecture?**
(The "architecture" means a pipeline managing recent dataset)
Thanks for reading.
Edited by: hdseo on Aug 1, 2021 12:09 AM
Edited by: hdseo on Aug 1, 2021 12:22 AM
Edited by: hdseo on Aug 1, 2021 12:26 AM
Accepted AnswerAmazon Personalize
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asked 10 months ago
Does a Personalize model need re-training before a new user's attributes are reflected in filtering?
I'm considering using the `User-Personalization` recipe with the new [PutItems](https://docs.aws.amazon.com/personalize/latest/dg/API_UBS_PutItems.html) and [PutUsers](https://docs.aws.amazon.com/personalize/latest/dg/API_UBS_PutUsers.html) APIs, but with requirements on making sure that **new users whose metadata is known** receive only appropriate recommendations.
For example after initial sign-up a user's country/age/membership status/etc are known and may be posted to Personalize `PutUsers`...
As I understand the filtering mechanism is quite separate from the personalization model, but then I think in the past I heard of some differences between how new users and new items get picked up in modelling.
Will new users' attributes be reflected in recommendation filters straight away (after the typical <15min near-real-time delay as for new/updated items?)
Or would new users continue to receive out-of-filter recommendations until the next model re-train? Maybe even until the next `FULL` model re-train, if an [UPDATE training](https://docs.aws.amazon.com/personalize/latest/dg/API_CreateSolutionVersion.html) is not sufficient to onboard new users?
Accepted AnswerAmazon Personalize
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