RecommendItemsToUser

java.lang.Object
- com.recombee.api_client.api_requests.Request
- - com.recombee.api_client.api_requests.RecommendItemsToUser

```
public class RecommendItemsToUser
extends Request
```
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](https://docs.recombee.com/admin_ui.html#reported-metrics). - Get subsequent recommended items when the user scrolls down (*infinite scroll*) or goes to the next page. See [Recommend Next Items](https://docs.recombee.com/api.html#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.

Field Summary

Fields
Modifier and Type	Field and Description
`protected java.lang.String`	`booster` Number-returning [ReQL](https://docs.recombee.com/reql.html) expression which allows you to boost recommendation rate of some items based on the values of their attributes.
`protected java.lang.Boolean`	`cascadeCreate` If the user does not exist in the database, returns a list of non-personalized recommendations and creates the user in the database.
`protected java.lang.Long`	`count` Number of items to be recommended (N for the top-N recommendation).
`protected java.lang.Double`	`diversity` Expert option Real number from [0.0, 1.0] which determines how much mutually dissimilar should the recommended items be.
`protected java.util.Map<java.lang.String,java.lang.Object>`	`expertSettings` Dictionary of custom options.
`protected java.lang.String`	`filter` Boolean-returning [ReQL](https://docs.recombee.com/reql.html) expression which allows you to filter recommended items based on the values of their attributes.
`protected java.lang.String[]`	`includedProperties` Allows to specify, which properties should be returned when `returnProperties=true` is set.
`protected Logic`	`logic` Logic specifies particular behavior of the recommendation models.
`protected java.lang.String`	`minRelevance` Expert option Specifies the threshold of how much relevant must the recommended items be to the user.
`protected java.lang.Boolean`	`returnAbGroup` If there is a custom AB-testing running, return name of group to which the request belongs.
`protected java.lang.Boolean`	`returnProperties` With `returnProperties=true`, property values of the recommended items are returned along with their IDs in a JSON dictionary.
`protected java.lang.Double`	`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.
`protected java.lang.Double`	`rotationTime` Expert option Taking rotationRate into account, specifies how long time it takes to an item to recover from the penalization.
`protected java.lang.String`	`scenario` Scenario defines a particular application of recommendations.
`protected java.lang.String`	`userId` ID of the user for whom personalized recommendations are to be generated.

Fields inherited from class com.recombee.api_client.api_requests.Request
timeout

Constructor Summary

Constructors
Constructor and Description

RecommendItemsToUser(java.lang.String userId, long count)
Construct the request

Constructors
Constructor and Description
`RecommendItemsToUser(java.lang.String userId, long count)` Construct the request

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`java.util.Map<java.lang.String,java.lang.Object>`	`getBodyParameters()` Get body parameters
`java.lang.String`	`getBooster()`
`boolean`	`getCascadeCreate()`
`long`	`getCount()`
`double`	`getDiversity()`
`java.util.Map<java.lang.String,java.lang.Object>`	`getExpertSettings()`
`java.lang.String`	`getFilter()`
`HTTPMethod`	`getHTTPMethod()`
`java.lang.String[]`	`getIncludedProperties()`
`Logic`	`getLogic()`
`java.lang.String`	`getMinRelevance()`
`java.lang.String`	`getPath()`
`java.util.Map<java.lang.String,java.lang.Object>`	`getQueryParameters()` Get query parameters
`boolean`	`getReturnAbGroup()`
`boolean`	`getReturnProperties()`
`double`	`getRotationRate()`
`double`	`getRotationTime()`
`java.lang.String`	`getScenario()`
`java.lang.String`	`getUserId()`
`RecommendItemsToUser`	`setBooster(java.lang.String booster)`
`RecommendItemsToUser`	`setCascadeCreate(boolean cascadeCreate)`
`RecommendItemsToUser`	`setDiversity(double diversity)`
`RecommendItemsToUser`	`setExpertSettings(java.util.Map<java.lang.String,java.lang.Object> expertSettings)`
`RecommendItemsToUser`	`setFilter(java.lang.String filter)`
`RecommendItemsToUser`	`setIncludedProperties(java.lang.String[] includedProperties)`
`RecommendItemsToUser`	`setLogic(Logic logic)`
`RecommendItemsToUser`	`setMinRelevance(java.lang.String minRelevance)`
`RecommendItemsToUser`	`setReturnAbGroup(boolean returnAbGroup)`
`RecommendItemsToUser`	`setReturnProperties(boolean returnProperties)`
`RecommendItemsToUser`	`setRotationRate(double rotationRate)`
`RecommendItemsToUser`	`setRotationTime(double rotationTime)`
`RecommendItemsToUser`	`setScenario(java.lang.String scenario)`

Methods inherited from class com.recombee.api_client.api_requests.Request
getEnsureHttps, getTimeout, setTimeout

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - userId
```
protected java.lang.String userId
```
    ID of the user for whom personalized recommendations are to be generated.
  - count
```
protected java.lang.Long count
```
    Number of items to be recommended (N for the top-N recommendation).
  - scenario
```
protected java.lang.String 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](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com). 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
```
protected java.lang.Boolean 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
```
protected java.lang.Boolean 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 } ```
  - includedProperties
```
protected java.lang.String[] 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 } ```
  - filter
```
protected java.lang.String filter
```
    Boolean-returning [ReQL](https://docs.recombee.com/reql.html) expression which allows you to filter recommended items based on the values of their attributes. Filters can be also assigned to a [scenario](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com).
  - booster
```
protected java.lang.String booster
```
    Number-returning [ReQL](https://docs.recombee.com/reql.html) 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](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com).
  - logic
```
protected Logic logic
```
    Logic specifies particular behavior of the recommendation models. You can pick tailored logic for your domain and use case. See [this section](https://docs.recombee.com/recommendation_logics.html) 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](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com).
  - diversity
```
protected java.lang.Double 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
```
protected java.lang.String 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
```
protected java.lang.Double 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
```
protected java.lang.Double 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
```
protected java.util.Map<java.lang.String,java.lang.Object> expertSettings
```
    Dictionary of custom options.
  - returnAbGroup
```
protected java.lang.Boolean returnAbGroup
```
    If there is a custom AB-testing running, return name of group to which the request belongs.
- Constructor Detail
  - RecommendItemsToUser
```
public RecommendItemsToUser(java.lang.String userId,
                            long count)
```
    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).
- Method Detail
  - setScenario
```
public RecommendItemsToUser setScenario(java.lang.String scenario)
```
    Parameters:
    
    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](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com). 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.
  - setCascadeCreate
```
public RecommendItemsToUser setCascadeCreate(boolean cascadeCreate)
```
    Parameters:
    
    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.
  - setReturnProperties
```
public RecommendItemsToUser setReturnProperties(boolean returnProperties)
```
    Parameters:
    
    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 } ```
  - setIncludedProperties
```
public RecommendItemsToUser setIncludedProperties(java.lang.String[] includedProperties)
```
    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 } ```
  - setFilter
```
public RecommendItemsToUser setFilter(java.lang.String filter)
```
    Parameters:
    
    filter - Boolean-returning [ReQL](https://docs.recombee.com/reql.html) expression which allows you to filter recommended items based on the values of their attributes. Filters can be also assigned to a [scenario](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com).
  - setBooster
```
public RecommendItemsToUser setBooster(java.lang.String booster)
```
    Parameters:
    
    booster - Number-returning [ReQL](https://docs.recombee.com/reql.html) 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](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com).
  - setLogic
```
public RecommendItemsToUser setLogic(Logic logic)
```
    Parameters:
    
    logic - Logic specifies particular behavior of the recommendation models. You can pick tailored logic for your domain and use case. See [this section](https://docs.recombee.com/recommendation_logics.html) 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](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com).
  - setDiversity
```
public RecommendItemsToUser setDiversity(double diversity)
```
    Parameters:
    
    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.
  - setMinRelevance
```
public RecommendItemsToUser setMinRelevance(java.lang.String minRelevance)
```
    Parameters:
    
    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.
  - setRotationRate
```
public RecommendItemsToUser setRotationRate(double rotationRate)
```
    Parameters:
    
    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`.
  - setRotationTime
```
public RecommendItemsToUser setRotationTime(double rotationTime)
```
    Parameters:
    
    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`.
  - setExpertSettings
```
public RecommendItemsToUser setExpertSettings(java.util.Map<java.lang.String,java.lang.Object> expertSettings)
```
    Parameters:
    
    expertSettings - Dictionary of custom options.
  - setReturnAbGroup
```
public RecommendItemsToUser setReturnAbGroup(boolean returnAbGroup)
```
    Parameters:
    
    returnAbGroup - If there is a custom AB-testing running, return name of group to which the request belongs.
  - getUserId
```
public java.lang.String getUserId()
```
  - getCount
```
public long getCount()
```
  - getScenario
```
public java.lang.String getScenario()
```
  - getCascadeCreate
```
public boolean getCascadeCreate()
```
  - getReturnProperties
```
public boolean getReturnProperties()
```
  - getIncludedProperties
```
public java.lang.String[] getIncludedProperties()
```
  - getFilter
```
public java.lang.String getFilter()
```
  - getBooster
```
public java.lang.String getBooster()
```
  - getLogic
```
public Logic getLogic()
```
  - getDiversity
```
public double getDiversity()
```
  - getMinRelevance
```
public java.lang.String getMinRelevance()
```
  - getRotationRate
```
public double getRotationRate()
```
  - getRotationTime
```
public double getRotationTime()
```
  - getExpertSettings
```
public java.util.Map<java.lang.String,java.lang.Object> getExpertSettings()
```
  - getReturnAbGroup
```
public boolean getReturnAbGroup()
```
  - getHTTPMethod
```
public HTTPMethod getHTTPMethod()
```
    Specified by:
    
    getHTTPMethod in class Request
    
    Returns:
    
    Used HTTP method
  - getPath
```
public java.lang.String getPath()
```
    Specified by:
    
    getPath in class Request
    
    Returns:
    
    URI to the endpoint including path parameters
  - getQueryParameters
```
public java.util.Map<java.lang.String,java.lang.Object> getQueryParameters()
```
    Get query parameters
    
    Specified by:
    
    getQueryParameters in class Request
    
    Returns:
    
    Values of query parameters (name of parameter: value of the parameter)
  - getBodyParameters
```
public java.util.Map<java.lang.String,java.lang.Object> getBodyParameters()
```
    Get body parameters
    
    Specified by:
    
    getBodyParameters in class Request
    
    Returns:
    
    Values of body parameters (name of parameter: value of the parameter)

Class RecommendItemsToUser

Field Summary

Fields inherited from class com.recombee.api_client.api_requests.Request

Constructor Summary

Method Summary

Methods inherited from class com.recombee.api_client.api_requests.Request

Methods inherited from class java.lang.Object

Field Detail

userId

count

scenario

cascadeCreate

returnProperties

includedProperties

filter

booster

logic

diversity

minRelevance

rotationRate

rotationTime

expertSettings

returnAbGroup

Constructor Detail

RecommendItemsToUser

Method Detail

setScenario

setCascadeCreate

setReturnProperties

setIncludedProperties

setFilter

setBooster

setLogic

setDiversity

setMinRelevance

setRotationRate

setRotationTime

setExpertSettings

setReturnAbGroup

getUserId

getCount

getScenario

getCascadeCreate

getReturnProperties

getIncludedProperties

getFilter

getBooster

getLogic

getDiversity

getMinRelevance

getRotationRate

getRotationTime

getExpertSettings

getReturnAbGroup

getHTTPMethod

getPath

getQueryParameters

getBodyParameters