Recommend items to user More...

Inheritance diagram for Recombee.ApiClient.ApiRequests.RecommendItemsToUser:

Collaboration diagram for Recombee.ApiClient.ApiRequests.RecommendItemsToUser:

Public Member Functions
	RecommendItemsToUser (string userId, long count, string scenario=null, bool? cascadeCreate=null, bool? returnProperties=null, string[] includedProperties=null, string filter=null, string booster=null, Logic logic=null, double? diversity=null, string minRelevance=null, double? rotationRate=null, double? rotationTime=null, Dictionary< string, object > expertSettings=null, bool? returnAbGroup=null)
	Construct the request More...

override string	Path ()
	Returns URI to the endpoint including path parameters More...

override Dictionary< string, object >	QueryParameters ()
	Get query parameters More...

override Dictionary< string, object >	BodyParameters ()
	Get body parameters More...

Public Member Functions inherited from Recombee.ApiClient.ApiRequests.Request
	Request (HttpMethod httpMethod, int timeoutMilliseconds, bool ensureHttps=false)
	Construct the request More...

Properties
string	UserId `[get]`
	ID of the user for whom personalized recommendations are to be generated. More...

long	Count `[get]`
	Number of items to be recommended (N for the top-N recommendation). More...

string	Scenario `[get]`
	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 performance of each scenario in the Admin 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. More...

bool?	CascadeCreate `[get]`
	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. More...

bool?	ReturnProperties `[get]`
	With `returnProperties=true`, property values of the recommended items are returned along with their IDs in a JSON dictionary. The acquired property values can be used for easy displaying of the recommended items to the user. Example response: More...

string[]	IncludedProperties `[get]`
	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=description,price`: More...

string	Filter `[get]`
	Boolean-returning ReQL expression which allows you to filter recommended items based on the values of their attributes. Filters can be also assigned to a scenario in the Admin UI. More...

string	Booster `[get]`
	Number-returning ReQL expression which allows you to boost recommendation rate of some items based on the values of their attributes. Boosters can be also assigned to a scenario in the Admin UI. More...

Logic	Logic `[get]`
	Logic specifies particular behavior of the recommendation models. You can pick tailored logic for your domain and use case. See this section for list of available logics and other details. The difference between `logic` and `scenario` is that `logic` specifies mainly behavior, while `scenario` specifies the place where recommendations are shown to the users. Logic can be also set to a scenario in the Admin UI. More...

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

string	MinRelevance `[get]`
	Expert option Specifies the threshold of how much relevant must the recommended items be to the user. Possible values one of: "low", "medium", "high". The default value is "low", meaning that the system attempts to recommend number of items equal to count at any cost. If there are not enough data (such as interactions or item 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 items of at least the requested relevance, and may return less than count items when there is not enough data to fulfill it. More...

double?	RotationRate `[get]`
	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 item 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 items. Default: `0`. More...

double?	RotationTime `[get]`
	Expert option Taking rotationRate into account, specifies how long time it takes to an item to recover from the penalization. For example, `rotationTime=7200.0` means that items recommended less than 2 hours ago are penalized. Default: `7200.0`. More...

Dictionary< string, object >	ExpertSettings `[get]`
	Dictionary of custom options. More...

bool?	ReturnAbGroup `[get]`
	If there is a custom AB-testing running, return name of group to which the request belongs. More...

Properties inherited from Recombee.ApiClient.ApiRequests.Request
TimeSpan	Timeout `[get, set]`
	Timeout for the request in milliseconds More...

bool	EnsureHttps `[get]`
	If true, HTTPS must be chosen over HTTP for this request More...

HttpMethod	RequestHttpMehod `[get]`
	Used HTTP method More...

Additional Inherited Members
Protected Member Functions inherited from Recombee.ApiClient.ApiRequests.Request
double	ConvertToUnixTimestamp (DateTime date)
	Returns Converts DateTime to UNIX timestamp (epoch) More...

Detailed Description

Recommend items to user

Based on user's past interactions (purchases, ratings, etc.) with the items, recommends top-N items that are most likely to be of high value for a given user. The most typical use cases are recommendations at homepage, in some "Picked just for you" section or in email. The returned items are sorted by relevance (first item being the most relevant). Besides the recommended items, also a unique recommId is returned in the response. It can be used to:

Let Recombee know that this recommendation was successful (e.g. user clicked one of the recommended items). See Reported metrics.
Get subsequent recommended items when the user scrolls down (infinite scroll) or goes to the next page. See Recommend Next Items. It is also possible to use POST HTTP method (for example in case of very long ReQL filter) - query parameters then become body parameters.

Constructor & Destructor Documentation

◆ RecommendItemsToUser()

Recombee.ApiClient.ApiRequests.RecommendItemsToUser.RecommendItemsToUser	(	string	userId,
		long	count,
		string	scenario = `null`,
		bool?	cascadeCreate = `null`,
		bool?	returnProperties = `null`,
		string[]	includedProperties = `null`,
		string	filter = `null`,
		string	booster = `null`,
		Logic	logic = `null`,
		double?	diversity = `null`,
		string	minRelevance = `null`,
		double?	rotationRate = `null`,
		double?	rotationTime = `null`,
		Dictionary< string, object >	expertSettings = `null`,
		bool?	returnAbGroup = `null`
	)

inline

Construct the request

Parameters

userId	ID of the user for whom personalized recommendations are to be generated.
count	Number of items to be recommended (N for the top-N recommendation).
scenario	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 performance of each scenario in the Admin 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.
cascadeCreate	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.
returnProperties	With `returnProperties=true`, property values of the recommended items are returned along with their IDs in a JSON dictionary. The acquired property values can be used for easy displaying of the recommended items to the user. Example response: { "recommId": "ce52ada4-e4d9-4885-943c-407db2dee837", "recomms": [ { "id": "tv-178", "values": { "description": "4K TV with 3D feature", "categories": ["Electronics", "Televisions"], "price": 342, "url": "myshop.com/tv-178" } }, { "id": "mixer-42", "values": { "description": "Stainless Steel Mixer", "categories": ["Home & Kitchen"], "price": 39, "url": "myshop.com/mixer-42" } } ], "numberNextRecommsCalls": 0 }

Parameters

includedProperties

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=description,price:

{
  "recommId": "a86ee8d5-cd8e-46d1-886c-8b3771d0520b",
  "recomms":
    [
      {
        "id": "tv-178",
        "values": {
          "description": "4K TV with 3D feature",
          "price": 342
        }
      },
      {
        "id": "mixer-42",
        "values": {
          "description": "Stainless Steel Mixer",
          "price": 39
        }
      }
    ],
  "numberNextRecommsCalls": 0
}

Parameters

filter	Boolean-returning ReQL expression which allows you to filter recommended items based on the values of their attributes. Filters can be also assigned to a scenario in the Admin UI.
booster	Number-returning ReQL expression which allows you to boost recommendation rate of some items based on the values of their attributes. Boosters can be also assigned to a scenario in the Admin UI.
logic	Logic specifies particular behavior of the recommendation models. You can pick tailored logic for your domain and use case. See this section for list of available logics and other details. The difference between `logic` and `scenario` is that `logic` specifies mainly behavior, while `scenario` specifies the place where recommendations are shown to the users. Logic can be also set to a scenario in the Admin UI.
diversity	Expert option Real number from [0.0, 1.0] which determines how much mutually dissimilar should the recommended items be. The default value is 0.0, i.e., no diversification. Value 1.0 means maximal diversification.
minRelevance	Expert option Specifies the threshold of how much relevant must the recommended items be to the user. Possible values one of: "low", "medium", "high". The default value is "low", meaning that the system attempts to recommend number of items equal to count at any cost. If there are not enough data (such as interactions or item 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 items of at least the requested relevance, and may return less than count items when there is not enough data to fulfill it.
rotationRate	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 item 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 items. Default: `0`.
rotationTime	Expert option Taking rotationRate into account, specifies how long time it takes to an item to recover from the penalization. For example, `rotationTime=7200.0` means that items recommended less than 2 hours ago are penalized. Default: `7200.0`.
expertSettings	Dictionary of custom options.
returnAbGroup	If there is a custom AB-testing running, return name of group to which the request belongs.

Member Function Documentation

◆ BodyParameters()

override Dictionary<string, object> Recombee.ApiClient.ApiRequests.RecommendItemsToUser.BodyParameters ( )

inlinevirtual

Get body parameters

Returns: Dictionary containing values of body parameters (name of parameter: value of the parameter)

Implements Recombee.ApiClient.ApiRequests.Request.

◆ Path()

override string Recombee.ApiClient.ApiRequests.RecommendItemsToUser.Path ( )

inlinevirtual

Returns: URI to the endpoint including path parameters

Implements Recombee.ApiClient.ApiRequests.Request.

◆ QueryParameters()

override Dictionary<string, object> Recombee.ApiClient.ApiRequests.RecommendItemsToUser.QueryParameters ( )

inlinevirtual

Get query parameters

Returns: Dictionary containing values of query parameters (name of parameter: value of the parameter)

Implements Recombee.ApiClient.ApiRequests.Request.

Property Documentation

◆ Booster

string Recombee.ApiClient.ApiRequests.RecommendItemsToUser.Booster

get

Number-returning ReQL expression which allows you to boost recommendation rate of some items based on the values of their attributes. Boosters can be also assigned to a scenario in the Admin UI.

◆ CascadeCreate

bool? Recombee.ApiClient.ApiRequests.RecommendItemsToUser.CascadeCreate

get

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.

◆ Count

long Recombee.ApiClient.ApiRequests.RecommendItemsToUser.Count

get

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

◆ Diversity

double? Recombee.ApiClient.ApiRequests.RecommendItemsToUser.Diversity

get

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

◆ ExpertSettings

Dictionary<string, object> Recombee.ApiClient.ApiRequests.RecommendItemsToUser.ExpertSettings

get

Dictionary of custom options.

◆ Filter

string Recombee.ApiClient.ApiRequests.RecommendItemsToUser.Filter

get

Boolean-returning ReQL expression which allows you to filter recommended items based on the values of their attributes. Filters can be also assigned to a scenario in the Admin UI.

◆ IncludedProperties

string [] Recombee.ApiClient.ApiRequests.RecommendItemsToUser.IncludedProperties

get

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=description,price:

{
  "recommId": "a86ee8d5-cd8e-46d1-886c-8b3771d0520b",
  "recomms":
    [
      {
        "id": "tv-178",
        "values": {
          "description": "4K TV with 3D feature",
          "price": 342
        }
      },
      {
        "id": "mixer-42",
        "values": {
          "description": "Stainless Steel Mixer",
          "price": 39
        }
      }
    ],
  "numberNextRecommsCalls": 0
}

◆ Logic

Logic Recombee.ApiClient.ApiRequests.RecommendItemsToUser.Logic

get

Logic specifies particular behavior of the recommendation models. You can pick tailored logic for your domain and use case. See this section for list of available logics and other details. The difference between logic and scenario is that logic specifies mainly behavior, while scenario specifies the place where recommendations are shown to the users. Logic can be also set to a scenario in the Admin UI.

◆ MinRelevance

string Recombee.ApiClient.ApiRequests.RecommendItemsToUser.MinRelevance

get

**Expert option** Specifies the threshold of how much relevant must the recommended items be to the user. Possible values one of: "low", "medium", "high". The default value is "low", meaning that the system attempts to recommend number of items equal to count at any cost. If there are not enough data (such as interactions or item 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 items of at least the requested relevance, and may return less than count items when there is not enough data to fulfill it.

◆ ReturnAbGroup

bool? Recombee.ApiClient.ApiRequests.RecommendItemsToUser.ReturnAbGroup

get

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

◆ ReturnProperties

bool? Recombee.ApiClient.ApiRequests.RecommendItemsToUser.ReturnProperties

get

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

{
  "recommId": "ce52ada4-e4d9-4885-943c-407db2dee837",
  "recomms": 
    [
      {
        "id": "tv-178",
        "values": {
          "description": "4K TV with 3D feature",
          "categories":   ["Electronics", "Televisions"],
          "price": 342,
          "url": "myshop.com/tv-178"
        }
      },
      {
        "id": "mixer-42",
        "values": {
          "description": "Stainless Steel Mixer",
          "categories":   ["Home & Kitchen"],
          "price": 39,
          "url": "myshop.com/mixer-42"
        }
      }
    ],
   "numberNextRecommsCalls": 0
}

◆ RotationRate

double? Recombee.ApiClient.ApiRequests.RecommendItemsToUser.RotationRate

get

**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 item 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 items. Default: 0.

◆ RotationTime

double? Recombee.ApiClient.ApiRequests.RecommendItemsToUser.RotationTime

get

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

◆ Scenario

string Recombee.ApiClient.ApiRequests.RecommendItemsToUser.Scenario

get

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 performance of each scenario in the Admin 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.

◆ UserId

string Recombee.ApiClient.ApiRequests.RecommendItemsToUser.UserId

get

ID of the user for whom personalized recommendations are to be generated.

The documentation for this class was generated from the following file:

Src/Recombee.ApiClient/ApiRequests/RecommendItemsToUser.cs

Public Member Functions

Properties

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ RecommendItemsToUser()

Member Function Documentation

◆ BodyParameters()

◆ Path()

◆ QueryParameters()

Property Documentation

◆ Booster

◆ CascadeCreate

◆ Count

◆ Diversity

◆ ExpertSettings

◆ Filter

◆ IncludedProperties

◆ Logic

◆ MinRelevance

◆ ReturnAbGroup

◆ ReturnProperties

◆ RotationRate

◆ RotationTime

◆ Scenario

◆ UserId