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# Exemples de résultats de tâches d'inférence par lots
<a name="batch-inference-job-output-examples"></a>

Lorsque vous créez une tâche d'inférence par lots, la tâche importe vos données d'entrée par lots depuis un compartiment Amazon S3, utilise la version de votre solution pour générer des *recommandations d'articles* et exporte les recommandations vers un compartiment Amazon S3 au format JSON. 

Les sections suivantes répertorient des exemples de fichiers de sortie pour les tâches d'inférence par lots par type de recette. Vous ne pouvez pas obtenir de recommandations par lots avec le Trending-Now ou les recettes. Next-Best-Action

**Topics**
+ [Recettes USER\$1PERSONALIZATION (PERSONNALISATION DE L'UTILISATEUR)](#batch-inference-output-user-personalization)
+ [recettes POPULAR\$1ITEMS](#batch-inference-output-popular-items)
+ [Recettes PERSONALIZED\$1RANKING](#batch-inference-output-personalized-ranking)
+ [Recettes RELATED\$1ITEMS](#batch-inference-output-related-items)

## Recettes USER\$1PERSONALIZATION (PERSONNALISATION DE L'UTILISATEUR)
<a name="batch-inference-output-user-personalization"></a>

 Voici un exemple de fichier JSON de sortie pour une recette USER\$1PERSONALIZATION. 

```
{"input":{"userId":"4638"},"output":{"recommendedItems":["63992","115149","110102","148626","148888","31685","102445","69526","92535","143355","62374","7451","56171","122882","66097","91542","142488","139385","40583","71530","39292","111360","34048","47099","135137"],"scores":[0.0152238,0.0069081,0.0068222,0.006394,0.0059746,0.0055851,0.0049357,0.0044644,0.0042968,0.004015,0.0038805,0.0037476,0.0036563,0.0036178,0.00341,0.0033467,0.0033258,0.0032454,0.0032076,0.0031996,0.0029558,0.0029021,0.0029007,0.0028837,0.0028316]},"error":null}
{"input":{"userId":"663"},"output":{"recommendedItems":["368","377","25","780","1610","648","1270","6","165","1196","1097","300","1183","608","104","474","736","293","141","2987","1265","2716","223","733","2028"],"scores":[0.0406197,0.0372557,0.0254077,0.0151975,0.014991,0.0127175,0.0124547,0.0116712,0.0091098,0.0085492,0.0079035,0.0078995,0.0075598,0.0074876,0.0072006,0.0071775,0.0068923,0.0066552,0.0066232,0.0062504,0.0062386,0.0061121,0.0060942,0.0060781,0.0059263]},"error":null}
{"input":{"userId":"3384"},"output":{"recommendedItems":["597","21","223","2144","208","2424","594","595","920","104","520","367","2081","39","1035","2054","160","1370","48","1092","158","2671","500","474","1907"],"scores":[0.0241061,0.0119394,0.0118012,0.010662,0.0086972,0.0079428,0.0073218,0.0071438,0.0069602,0.0056961,0.0055999,0.005577,0.0054387,0.0051787,0.0051412,0.0050493,0.0047126,0.0045393,0.0042159,0.0042098,0.004205,0.0042029,0.0040778,0.0038897,0.0038809]},"error":null}
...
```

## recettes POPULAR\$1ITEMS
<a name="batch-inference-output-popular-items"></a>

 L'exemple suivant montre le format du fichier JSON de sortie pour la recette Popularity-Count. Vous ne pouvez pas obtenir de recommandations par lots avec la recette Trending-Now. 

```
{"input": {"userId": "12"}, "output": {"recommendedItems": ["105", "106", "441"]}}
{"input": {"userId": "105"}, "output": {"recommendedItems": ["105", "106", "441"]}}
{"input": {"userId": "41"}, "output": {"recommendedItems": ["105", "106", "441"]}}
...
```

## Recettes PERSONALIZED\$1RANKING
<a name="batch-inference-output-personalized-ranking"></a>

 L'exemple suivant montre le format du fichier JSON de sortie pour une recette PERSONALIZED\$1RANKING. 

```
{"input":{"userId":"891","itemList":["27","886","101"]},"output":{"recommendedItems":["27","101","886"],"scores":[0.48421,0.28133,0.23446]}}
{"input":{"userId":"445","itemList":["527","55","901"]},"output":{"recommendedItems":["901","527","55"],"scores":[0.46972,0.31011,0.22017]}}
{"input":{"userId":"71","itemList":["29","351","199"]},"output":{"recommendedItems":["351","29","199"],"scores":[0.68937,0.24829,0.06232]}}
...
```

## Recettes RELATED\$1ITEMS
<a name="batch-inference-output-related-items"></a>

 L'exemple suivant montre le format du fichier JSON de sortie pour une recette RELATED\$1ITEMS. 

```
{"input": {"itemId": "105"}, "output": {"recommendedItems": ["106", "107", "49"]}}
{"input": {"itemId": "106"}, "output": {"recommendedItems": ["105", "107", "49"]}}
{"input": {"itemId": "441"}, "output": {"recommendedItems": ["2", "442", "435"]}}
...
```

 L'exemple suivant montre le format du fichier JSON de sortie pour la recette Similar-Items avec thèmes. Pour plus d'informations sur les recommandations avec des thèmes, consultez[Recommandations par lots avec des thèmes issus du générateur de contenu](themed-batch-recommendations.md). 

```
{"input":{"itemId":"40"},"output":{"recommendedItems":["36","50","44","22","21","29","3","1","2","39"],"theme":"Movies with a strong female lead","itemsThemeRelevanceScores":[0.19994527,0.183059963,0.17478035,0.1618133,0.1574806,0.15468733,0.1499242,0.14353688,0.13531424,0.10291852]}}
{"input":{"itemId":"43"},"output":{"recommendedItems":["50","21","36","3","17","2","39","1","10","5"],"theme":"The best movies of 1995","itemsThemeRelevanceScores":[0.184988,0.1795761,0.11143453,0.0989443,0.08258403,0.07952615,0.07115086,0.0621634,-0.138913,-0.188913]}}
...
```