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[ aws . personalize-runtime ]

get-personalized-ranking

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.

Note

The solution backing the campaign must have been created using a recipe of type PERSONALIZED_RANKING.

See also: AWS API Documentation

Synopsis

  get-personalized-ranking
--campaign-arn <value>
--input-list <value>
--user-id <value>
[--context <value>]
[--filter-arn <value>]
[--filter-values <value>]
[--metadata-columns <value>]
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]
[--debug]
[--endpoint-url <value>]
[--no-verify-ssl]
[--no-paginate]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--no-sign-request]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]

Options

--campaign-arn (string)

The Amazon Resource Name (ARN) of the campaign to use for generating the personalized ranking.

--input-list (list)

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.

(string)

Syntax:

"string" "string" ...

--user-id (string)

The user for which you want the campaign to provide a personalized ranking.

--context (map)

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.

key -> (string)

value -> (string)

Shorthand Syntax:

KeyName1=string,KeyName2=string

JSON Syntax:

{"string": "string"
  ...}

--filter-arn (string)

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 .

--filter-values (map)

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 .

key -> (string)

value -> (string)

Shorthand Syntax:

KeyName1=string,KeyName2=string

JSON Syntax:

{"string": "string"
  ...}

--metadata-columns (map)

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 .

key -> (string)

value -> (list)

(string)

Shorthand Syntax:

KeyName1=string,string,KeyName2=string,string

JSON Syntax:

{"string": ["string", ...]
  ...}

--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

Global Options

--debug (boolean)

Turn on debug logging.

--endpoint-url (string)

Override command's default URL with the given URL.

--no-verify-ssl (boolean)

By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.

--no-paginate (boolean)

Disable automatic pagination.

--output (string)

The formatting style for command output.

  • json
  • text
  • table

--query (string)

A JMESPath query to use in filtering the response data.

--profile (string)

Use a specific profile from your credential file.

--region (string)

The region to use. Overrides config/env settings.

--version (string)

Display the version of this tool.

--color (string)

Turn on/off color output.

  • on
  • off
  • auto

--no-sign-request (boolean)

Do not sign requests. Credentials will not be loaded if this argument is provided.

--ca-bundle (string)

The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.

--cli-read-timeout (int)

The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.

--cli-connect-timeout (int)

The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.

Output

personalizedRanking -> (list)

A list of items in order of most likely interest to the user. The maximum is 500.

(structure)

An object that identifies an item.

The and APIs return a list of PredictedItem s.

itemId -> (string)

The recommended item ID.

score -> (double)

A numeric representation of the model's certainty that the item will be the next user selection. For more information on scoring logic, see how-scores-work .

promotionName -> (string)

The name of the promotion that included the predicted item.

metadata -> (map)

Metadata about the item from your Items dataset.

key -> (string)

value -> (string)

recommendationId -> (string)

The ID of the recommendation.