# Getting a personalized ranking (custom resources)
<a name="rankings"></a>

A personalized ranking is a list of recommended items that are re-ranked for a specific user. To get personalized rankings, call the [GetPersonalizedRanking](API_RS_GetPersonalizedRanking.md) API operation or get recommendations from a campaign in the console.

**Note**  
The solution backing the campaign must have been created using a recipe of type PERSONALIZED\$1RANKING. For more information, see [Choosing a recipe](working-with-predefined-recipes.md).

**Topics**
+ [How personalized ranking scoring works](#how-ranking-scoring-works)
+ [Getting a personalized ranking (console)](get-ranking-recommendations-console.md)
+ [Getting a personalized ranking (Amazon CLI)](get-personalized-rankings-cli.md)
+ [Getting a personalized ranking (Amazon SDKs)](get-personalized-rankings-sdk.md)
+ [Personalized-Ranking sample notebook](#real-time-recommendations-personalized-ranking-example)

## How personalized ranking scoring works
<a name="how-ranking-scoring-works"></a>

Like the scores returned by the `GetRecommendations` operation for solutions created with the User-Personalization-v2 and User-Personalization recipes, `GetPersonalizedRanking` scores sum to 1, but only the input items receive scores and recommendation scores tend to be higher. If an item wasn't present during the latest training, it receives a score of 0.

Mathematically, the scoring function for GetPersonalizedRanking is identical to `GetRecommendations`, except that it only considers the input items. This means that scores closer to 1 become more likely, as there are fewer other choices to divide up the score:

![\[Depicts the formula used to calculate scores for each item in a ranking.\]](http://docs.amazonaws.cn/en_us/personalize/latest/dg/images/get_personalized_ranking.png)


## Personalized-Ranking sample notebook
<a name="real-time-recommendations-personalized-ranking-example"></a>

 For a sample Jupyter notebook that shows how to use the Personalized-Ranking recipe see [Personalize Ranking Example](https://github.com/aws-samples/amazon-personalize-samples/blob/master/next_steps/core_use_cases/personalized_ranking/personalize_ranking_example.ipynb).