PersonalizeRuntime / Client / get_personalized_ranking

get_personalized_ranking#

PersonalizeRuntime.Client.get_personalized_ranking(**kwargs)#

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

Request Syntax

response = client.get_personalized_ranking(
    campaignArn='string',
    inputList=[
        'string',
    ],
    userId='string',
    context={
        'string': 'string'
    },
    filterArn='string',
    filterValues={
        'string': 'string'
    },
    metadataColumns={
        'string': [
            'string',
        ]
    }
)
Parameters:

  • campaignArn (string) –

    [REQUIRED]

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

  • inputList (list) –

    [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.

    • (string) –

  • userId (string) –

    [REQUIRED]

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

  • context (dict) –

    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.

    • (string) –

      • (string) –

  • filterArn (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.

  • filterValues (dict) –

    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.

    • (string) –

      • (string) –

  • metadataColumns (dict) –

    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.

    • (string) –

      • (list) –

        • (string) –

Return type:

dict

Returns:

Response Syntax

{
    'personalizedRanking': [
        {
            'itemId': 'string',
            'score': 123.0,
            'promotionName': 'string',
            'metadata': {
                'string': 'string'
            },
            'reason': [
                'string',
            ]
        },
    ],
    'recommendationId': 'string'
}

Response Structure

  • (dict) –

    • personalizedRanking (list) –

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

      • (dict) –

        An object that identifies an item.

        The and APIs return a list of ``PredictedItem``s.

        • itemId (string) –

          The recommended item ID.

        • score (float) –

          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 (dict) –

          Metadata about the item from your Items dataset.

          • (string) –

            • (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.

Exceptions