[ 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 | --cli-input-yaml]
[--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>]
[--cli-binary-format <value>]
[--no-cli-pager]
[--cli-auto-prompt]
[--no-cli-auto-prompt]

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 | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those 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. This may not be specified along with --cli-input-yaml.

--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. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.

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. If automatic pagination is disabled, the AWS CLI will only make one call, for the first page of results.

--output (string)

The formatting style for command output.

• json
• text
• table
• yaml
• yaml-stream

--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.

--cli-binary-format (string)

The formatting style to be used for binary blobs. The default format is base64. The base64 format expects binary blobs to be provided as a base64 encoded string. The raw-in-base64-out format preserves compatibility with AWS CLI V1 behavior and binary values must be passed literally. When providing contents from a file that map to a binary blob fileb:// will always be treated as binary and use the file contents directly regardless of the cli-binary-format setting. When using file:// the file contents will need to properly formatted for the configured cli-binary-format.

• base64
• raw-in-base64-out

--no-cli-pager (boolean)

Disable cli pager for output.

--cli-auto-prompt (boolean)

Automatically prompt for CLI input parameters.

--no-cli-auto-prompt (boolean)

Disable automatically prompt for CLI input parameters.

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)

reason -> (list)

If you use User-Personalization-v2, a list of reasons for why the item was included in recommendations. Possible reasons include the following:

• Promoted item - Indicates the item was included as part of a promotion that you applied in your recommendation request.
• Exploration - Indicates the item was included with exploration. With exploration, recommendations include items with less interactions data or relevance for the user. For more information about exploration, see Exploration .
• Popular item - Indicates the item was included as a placeholder popular item. If you use a filter, depending on how many recommendations the filter removes, Amazon Personalize might add placeholder items to meet the numResults for your recommendation request. These items are popular items, based on interactions data, that satisfy your filter criteria. They don’t have a relevance score for the user.

(string)

recommendationId -> (string)

The ID of the recommendation.