RErecombee
Recommendations

Recommend Item Segments to Item

Recommends Segments from a Segmentation that are the most relevant to a particular item.

Based on the used Segmentation, this endpoint can be used for example for:

  • Recommending the related categories
  • Recommending the related genres
  • Recommending the related brands
  • Recommending the related artists

You need to set the used Segmentation the Admin UI in the Scenario settings prior to using this endpoint.

The returned segments are sorted by relevance (first segment being the most relevant).

It is also possible to use GET HTTP method - body parameters then become query parameters.

post/{databaseId}/recomms/items/{itemId}/item-segments/

Request

  • Base URL
    http://Based on the region of your database (see https://docs.recombee.com/regions).
  • URL
    http://Based on the region of your database (see https://docs.recombee.com/regions)./{databaseId}/recomms/items/{itemId}/item-segments/
  • Auth
    none declared

Path parameters

databaseIdstring required

ID of your database.

itemIdstring required

ID of the item for which the recommendations are to be generated.

Request body

targetUserIdstring required

ID of the user who will see the recommendations.

Specifying the targetUserId is beneficial because:

  • It makes the recommendations personalized
  • Allows the calculation of Actions and Conversions in the graphical user interface, as Recombee can pair the user who got recommendations and who afterward viewed/purchased an item.

If you insist on not specifying the user, pass null (None, nil, NULL etc., depending on the language) to targetUserId. Do not create some special dummy user for getting recommendations, as it could mislead the recommendation models, and result in wrong recommendations.

For anonymous/unregistered users, it is possible to use, for example, their session ID.

countinteger required

Number of item segments to be recommended (N for the top-N recommendation).

scenariostring

Scenario defines a particular application of recommendations. It can be, for example, "homepage", "cart", or "emailing".

You can set various settings to the scenario in the Admin UI. You can also see the performance of each scenario in the Admin UI separately, so you can check how well each application performs.

The AI that optimizes models to get the best results may optimize different scenarios separately or even use different models in each of the scenarios.

cascadeCreateboolean

If the user does not exist in the database, returns a list of non-personalized recommendations and creates the user in the database. This allows, for example, rotations in the following recommendations for that user, as the user will be already known to the system.

filterstring

Boolean-returning ReQL expression which allows you to filter recommended segments based on the segmentationId.

boosterstring

Number-returning ReQL expression which allows you to boost recommendation rate of some segments based on the segmentationId.

expertSettingsobject

Dictionary of custom options.

returnAbGroupboolean

If there is a custom AB-testing running, return the name of the group to which the request belongs.

reqlExpressionsobject

A dictionary of ReQL expressions that will be executed for each recommended Item Segment. This can be used to compute additional properties of the recommended Item Segments.

The keys are the names of the expressions, and the values are the actual ReQL expressions.

Example request:

{
  "reqlExpressions": {
    "countItems": "size(segment_items(\"categories\", 'segmentId'))"
  }
}

Example response:

{
  "recommId": "a7ac55a4-8d6e-4f19-addc-abac4164d8a8",
  "recomms": 
    [
      {
        "id": "category-fantasy-books",
        "reqlEvaluations": {
          "countItems": 486
        }
      },
      {
        "id": "category-sci-fi-costumes",
        "reqlEvaluations": {
          "countItems": 19
        }
      }
    ],
   "numberNextRecommsCalls": 0
}

Response

successful operation

recommIdstring required

Id of the recommendation request

numberNextRecommsCallsinteger

How many times Recommend Next Items have been called for this recommId

abGroupstring

Name of AB-testing group to which the request belongs if there is a custom AB-testing running.

Changes

No recorded changes to this operation across all 3 revisions of this API.