Filter expressions

Item interactions: You can use filter expressions to include or exclude items or users based on interactions data. For example, you can exclude items that a user has already clicked (for item recommendations), or include only users who have rated items (for the Item-Affinity recipe). For all recipe types, you can filter only based on event type. You can't filter based on other interaction metadata, such as contextual metadata. You can't use item interactions filters with the Item-Attribute-Affinity recipe.

Amazon Personalize considers up to 100 of the most recent interactions per user per event type. This is an adjustable quota. You can request a quota increase using the Service Quotas console. If you don't import item interactions for a user for three months, your filters no longer consider the user's historical data. To consider this data, you must import the user's entire event history again.

Action interactions: Use filter expressions to include or exclude actions that a user has interacted with based on event type. For example, you might exclude actions that a user has already taken. You can't filter based on other action interaction metadata.

Amazon Personalize considers up to 300 of the most recent action interactions per user per event type. This is an adjustable quota. You can request a quota increase using the Service Quotas console.

Items: Use filter expressions to include or exclude items based on specific item conditions. You can't use filters to include or exclude items based on unstructured textual item metadata such as product descriptions. If your domain use case or custom recipe generates related items recommendations, such as the Similar-Items recipe or the More Like X domain use case, you can use filter expressions to include or exclude items based on the properties of the item you specify in your recommendation request.

Users: For item and action recommendations, if you have a Users dataset, you can exclude or include items or actions based on a CurrentUser. For personalized recommendations, popular items, and action recommendations, this is the user you are getting recommendations for. For related items, this an optional user you can specify in your recommendation request.

For user segments, you can use filter expressions to include or exclude users from user segments based on attributes, such as Users.MEMBERSHIP_STATUS.

Actions: Use filter expressions to include or exclude actions based on specific action conditions. Amazon Personalize automatically excludes actions based on Action expiration timestamp and Repeat frequency data. You can't create additional custom filters that filter based on this data.