personalizeruntime_get_personalized_ranking: Re-ranks a list of recommended items for the given user

In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

Re-ranks a list of recommended items for the given user

Description

Re-ranks a list of recommended items for the given user. The first item in the list is deemed the most likely item to be of interest to the user.

See https://www.paws-r-sdk.com/docs/personalizeruntime_get_personalized_ranking/ for full documentation.

Usage

personalizeruntime_get_personalized_ranking(
  campaignArn,
  inputList,
  userId,
  context = NULL,
  filterArn = NULL,
  filterValues = NULL,
  metadataColumns = NULL
)

Arguments

campaignArn	[required] The Amazon Resource Name (ARN) of the campaign to use for generating the personalized ranking.
inputList	[required] A list of items (by itemId) to rank. If an item was not included in the training dataset, the item is appended to the end of the reranked list. If you are including metadata in recommendations, the maximum is 50. Otherwise, the maximum is 500.
userId	[required] The user for which you want the campaign to provide a personalized ranking.
context	The contextual metadata to use when getting recommendations. Contextual metadata includes any interaction information that might be relevant when getting a user's recommendations, such as the user's current location or device type.
filterArn	The Amazon Resource Name (ARN) of a filter you created to include items or exclude items from recommendations for a given user. For more information, see Filtering Recommendations.
filterValues	The values to use when filtering recommendations. For each placeholder parameter in your filter expression, provide the parameter name (in matching case) as a key and the filter value(s) as the corresponding value. Separate multiple values for one parameter with a comma. For filter expressions that use an INCLUDE element to include items, you must provide values for all parameters that are defined in the expression. For filters with expressions that use an EXCLUDE element to exclude items, you can omit the filter-values.In this case, Amazon Personalize doesn't use that portion of the expression to filter recommendations. For more information, see Filtering Recommendations.
metadataColumns	If you enabled metadata in recommendations when you created or updated the campaign, specify metadata columns from your Items dataset to include in the personalized ranking. The map key is ITEMS and the value is a list of column names from your Items dataset. The maximum number of columns you can provide is 10. For information about enabling metadata for a campaign, see Enabling metadata in recommendations for a campaign.

paws.machine.learning documentation built on Sept. 12, 2024, 6:23 a.m.