RecommendUsersToUser

Extends \Recombee\RecommApi\Requests\Request

Get similar users as some given user, based on the user's past interactions (purchases, ratings, etc.) and values of properties.

It is also possible to use POST HTTP method (for example in case of very long ReQL filter) - query parameters then become body parameters.

package

Default

Methods

Construct the request

__construct(string $user_id, integer $count, array $optional = array()) 
Throws
\Recombee\RecommApi\Requests\Exceptions\UnknownOptionalParameterException

UnknownOptionalParameterException if an unknown optional parameter is given in $optional

Arguments

$user_id

string

User to which we find similar users

$count

integer

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

$optional

array

Optional parameters given as an array containing pairs name of the parameter => value

  • Allowed parameters:
    • filter
      • Type: string
      • Description: Boolean-returning ReQL expression which allows you to filter recommended users based on the values of their attributes.
    • booster
      • Type: string
      • Description: Number-returning ReQL expression which allows you to boost recommendation rate of some users based on the values of their attributes.
    • cascadeCreate
      • Type: bool
      • Description: 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.
    • scenario
      • Type: string
      • Description: Scenario defines a particular application of recommendations. It can be for example "homepage", "cart" or "emailing". You can see each scenario in the UI separately, so you can check how well each application performs. The AI which optimizes models in order to get the best results may optimize different scenarios separately, or even use different models in each of the scenarios.
    • returnProperties
      • Type: bool
      • Description: With returnProperties=true, property values of the recommended users are returned along with their IDs in a JSON dictionary. The acquired property values can be used for easy displaying the recommended users. Example response:
        {
        "recommId": "9cb9c55d-50ba-4478-84fd-ab456136156e",
        "recomms":
        [
        {
        "id": "user-17",
        "values": {
        "country": "US",
        "sex": "F"
        }
        },
        {
        "id": "user-2",
        "values": {
        "country": "CAN",
        "sex": "M"
        }
        }
        ]
        }
    • includedProperties
      • Type: array
      • Description: Allows to specify, which properties should be returned when returnProperties=true is set. The properties are given as a comma-separated list. Example response for includedProperties=country:
        {
        "recommId": "b326d82d-5d57-4b45-b362-c9d6f0895855",
        "recomms":
        [
        {
        "id": "user-17",
        "values": {
        "country": "US"
        }
        },
        {
        "id": "user-2",
        "values": {
        "country": "CAN"
        }
        }
        ]
        }
    • diversity
      • Type: float
      • Description: Expert option Real number from [0.0, 1.0] which determines how much mutually dissimilar should the recommended users be. The default value is 0.0, i.e., no diversification. Value 1.0 means maximal diversification.
    • minRelevance
      • Type: string
      • Description: Expert option Specifies the threshold of how much relevant must the recommended users be. Possible values one of: "low", "medium", "high". The default value is "low", meaning that the system attempts to recommend number of users equal to count at any cost. If there are not enough data (such as interactions or user properties), this may even lead to bestseller-based recommendations to be appended to reach the full count. This behavior may be suppressed by using "medium" or "high" values. In such case, the system only recommends users of at least the requested relevancy, and may return less than count users when there is not enough data to fulfill it.
    • rotationRate
      • Type: float
      • Description: Expert option If your users browse the system in real-time, it may easily happen that you wish to offer them recommendations multiple times. Here comes the question: how much should the recommendations change? Should they remain the same, or should they rotate? Recombee API allows you to control this per-request in backward fashion. You may penalize an user for being recommended in the near past. For the specific user, rotationRate=1 means maximal rotation, rotationRate=0 means absolutely no rotation. You may also use, for example rotationRate=0.2 for only slight rotation of recommended users.
    • rotationTime
      • Type: float
      • Description: Expert option Taking rotationRate into account, specifies how long time it takes to an user to recover from the penalization. For example, rotationTime=7200.0 means that users recommended less than 2 hours ago are penalized.
    • expertSettings
      • Type:
      • Description: Dictionary of custom options.

Get body parameters

getBodyParameters() : array
inherited abstract

Response

array

Values of body parameters (name of parameter => value of the parameter)

Returns true if HTTPS must be chosen over HTTP for this request

getEnsureHttps() : boolean
inherited

Response

boolean

true if HTTPS must be chosen

Get used HTTP method

getMethod() : static
inherited abstract

Response

static

Used HTTP method

Get URI to the endpoint

getPath() : string
inherited abstract

Response

string

URI to the endpoint

Get query parameters

getQueryParameters() : array
inherited abstract

Response

array

Values of query parameters (name of parameter => value of the parameter)

Get request timeout

getTimeout() : integer
inherited

Response

integer

Request timeout in milliseconds

Sets if HTTPS must be chosen over HTTP for this request

setEnsureHttps( $ensure_https) 
inherited

Arguments

$ensure_https

Sets request timeout

setTimeout( $timeout) 
inherited

Arguments

$timeout

Properties

User to which we find similar users

user_id : string
var

User to which we find similar users

Type(s)

string

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

count : integer
var

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

Type(s)

integer

Boolean-returning [ReQL](https://docs.recombee.com/reql.html) expression which allows you to filter recommended users based on the values of their attributes.

filter : string
var

Boolean-returning ReQL expression which allows you to filter recommended users based on the values of their attributes.

Type(s)

string

Number-returning [ReQL](https://docs.recombee.com/reql.html) expression which allows you to boost recommendation rate of some users based on the values of their attributes.

booster : string
var

Number-returning ReQL expression which allows you to boost recommendation rate of some users based on the values of their attributes.

Type(s)

string

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.

cascade_create : boolean
var

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.

Type(s)

boolean

Scenario defines a particular application of recommendations. It can be for example "homepage", "cart" or "emailing". You can see each scenario in the UI separately, so you can check how well each application performs. The AI which optimizes models in order to get the best results may optimize different scenarios separately, or even use different models in each of the scenarios.

scenario : string
var

Scenario defines a particular application of recommendations. It can be for example "homepage", "cart" or "emailing". You can see each scenario in the UI separately, so you can check how well each application performs. The AI which optimizes models in order to get the best results may optimize different scenarios separately, or even use different models in each of the scenarios.

Type(s)

string

With `returnProperties=true`, property values of the recommended users are returned along with their IDs in a JSON dictionary. The acquired property values can be used for easy displaying the recommended users. Example response: ``` { "recommId": "9cb9c55d-50ba-4478-84fd-ab456136156e", "recomms": [ { "id": "user-17", "values": { "country": "US", "sex": "F" } }, { "id": "user-2", "values": { "country": "CAN", "sex": "M" } } ] } ```

return_properties : boolean
var

With returnProperties=true, property values of the recommended users are returned along with their IDs in a JSON dictionary. The acquired property values can be used for easy displaying the recommended users. Example response:

  {
    "recommId": "9cb9c55d-50ba-4478-84fd-ab456136156e",
    "recomms": 
      [
        {
          "id": "user-17",
          "values": {
            "country": "US",
            "sex": "F"
          }
        },
        {
          "id": "user-2",
          "values": {
            "country": "CAN",
            "sex": "M"
          }
        }
      ]
    }

Type(s)

boolean

Allows to specify, which properties should be returned when `returnProperties=true` is set. The properties are given as a comma-separated list. Example response for `includedProperties=country`: ``` { "recommId": "b326d82d-5d57-4b45-b362-c9d6f0895855", "recomms": [ { "id": "user-17", "values": { "country": "US" } }, { "id": "user-2", "values": { "country": "CAN" } } ] } ```

included_properties : array
var

Allows to specify, which properties should be returned when returnProperties=true is set. The properties are given as a comma-separated list. Example response for includedProperties=country:

  {
    "recommId": "b326d82d-5d57-4b45-b362-c9d6f0895855",
    "recomms":
      [
        {
          "id": "user-17",
          "values": {
            "country": "US"
          }
        },
        {
          "id": "user-2",
          "values": {
            "country": "CAN"
          }
        }
      ]
  }

Type(s)

array

**Expert option** Real number from [0.0, 1.0] which determines how much mutually dissimilar should the recommended users be. The default value is 0.0, i.e., no diversification. Value 1.0 means maximal diversification.

diversity : float
var

Expert option Real number from [0.0, 1.0] which determines how much mutually dissimilar should the recommended users be. The default value is 0.0, i.e., no diversification. Value 1.0 means maximal diversification.

Type(s)

float

**Expert option** Specifies the threshold of how much relevant must the recommended users be. Possible values one of: "low", "medium", "high". The default value is "low", meaning that the system attempts to recommend number of users equal to *count* at any cost. If there are not enough data (such as interactions or user properties), this may even lead to bestseller-based recommendations to be appended to reach the full *count*. This behavior may be suppressed by using "medium" or "high" values. In such case, the system only recommends users of at least the requested relevancy, and may return less than *count* users when there is not enough data to fulfill it.

min_relevance : string
var

Expert option Specifies the threshold of how much relevant must the recommended users be. Possible values one of: "low", "medium", "high". The default value is "low", meaning that the system attempts to recommend number of users equal to count at any cost. If there are not enough data (such as interactions or user properties), this may even lead to bestseller-based recommendations to be appended to reach the full count. This behavior may be suppressed by using "medium" or "high" values. In such case, the system only recommends users of at least the requested relevancy, and may return less than count users when there is not enough data to fulfill it.

Type(s)

string

**Expert option** If your users browse the system in real-time, it may easily happen that you wish to offer them recommendations multiple times. Here comes the question: how much should the recommendations change? Should they remain the same, or should they rotate? Recombee API allows you to control this per-request in backward fashion. You may penalize an user for being recommended in the near past. For the specific user, `rotationRate=1` means maximal rotation, `rotationRate=0` means absolutely no rotation. You may also use, for example `rotationRate=0.2` for only slight rotation of recommended users.

rotation_rate : float
var

Expert option If your users browse the system in real-time, it may easily happen that you wish to offer them recommendations multiple times. Here comes the question: how much should the recommendations change? Should they remain the same, or should they rotate? Recombee API allows you to control this per-request in backward fashion. You may penalize an user for being recommended in the near past. For the specific user, rotationRate=1 means maximal rotation, rotationRate=0 means absolutely no rotation. You may also use, for example rotationRate=0.2 for only slight rotation of recommended users.

Type(s)

float

**Expert option** Taking *rotationRate* into account, specifies how long time it takes to an user to recover from the penalization. For example, `rotationTime=7200.0` means that users recommended less than 2 hours ago are penalized.

rotation_time : float
var

Expert option Taking rotationRate into account, specifies how long time it takes to an user to recover from the penalization. For example, rotationTime=7200.0 means that users recommended less than 2 hours ago are penalized.

Type(s)

float

Dictionary of custom options.

expert_settings : 
var

Dictionary of custom options.

Type(s)

Array containing values of optional parameters

optional : array
var

Array containing values of optional parameters

Type(s)

array

Timeout of the request in milliseconds

timeout : integer
inherited
var

Timeout of the request in milliseconds

Type(s)

integer

Sets if the HTTPS must be chosen over HTTP for this request

ensure_https : boolean
inherited
var

Sets if the HTTPS must be chosen over HTTP for this request

Type(s)

boolean