2020/08/06 - Amazon Personalize Runtime - 2 updated api methods
Changes Add 'exploration' functionality
{'recommendationId': 'string'}
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
client.get_personalized_ranking(
campaignArn='string',
inputList=[
'string',
],
userId='string',
context={
'string': 'string'
},
filterArn='string'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) of the campaign to use for generating the personalized ranking.
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. The maximum is 500.
(string) --
string
[REQUIRED]
The user for which you want the campaign to provide a personalized ranking.
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) --
string
The Amazon Resource Name (ARN) of a filter you created to include or exclude items from recommendations for a given user.
dict
Response Syntax
{
'personalizedRanking': [
{
'itemId': 'string',
'score': 123.0
},
],
'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 .
recommendationId (string) --
The ID of the recommendation.
{'recommendationId': 'string'}
Returns a list of recommended items. The required input depends on the recipe type used to create the solution backing the campaign, as follows:
RELATED_ITEMS - itemId required, userId not used
USER_PERSONALIZATION - itemId optional, userId required
Note
Campaigns that are backed by a solution created using a recipe of type PERSONALIZED_RANKING use the API.
See also: AWS API Documentation
Request Syntax
client.get_recommendations(
campaignArn='string',
itemId='string',
userId='string',
numResults=123,
context={
'string': 'string'
},
filterArn='string'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) of the campaign to use for getting recommendations.
string
The item ID to provide recommendations for.
Required for RELATED_ITEMS recipe type.
string
The user ID to provide recommendations for.
Required for USER_PERSONALIZATION recipe type.
integer
The number of results to return. The default is 25. The maximum is 500.
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) --
string
The ARN of the filter to apply to the returned recommendations. For more information, see Using Filters with Amazon Personalize .
When using this parameter, be sure the filter resource is ACTIVE .
dict
Response Syntax
{
'itemList': [
{
'itemId': 'string',
'score': 123.0
},
],
'recommendationId': 'string'
}
Response Structure
(dict) --
itemList (list) --
A list of recommendations sorted in ascending order by prediction score. There can be a maximum of 500 items in the list.
(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 .
recommendationId (string) --
The ID of the recommendation.