Help Center> RES> API Reference> API> Scenario> Creating an Intelligent Scenario

Creating an Intelligent Scenario

Function

This API is used to create an intelligent scenario in a specified workspace.

URI

POST /v2.0/{project_id}/workspaces/{workspace_id}/intelligent-scenes

**Table 1** Path parameters
Parameter	Mandatory	Type	Description
project_id	Yes	String	Project ID. For details on how to obtain the project ID, see Obtaining a Project ID.
workspace_id	Yes	String	Workspace ID

**Table 2** Query parameters
Parameter	Mandatory	Type	Description
X-Auth-Token	Yes	String	User token. For details on how to obtain the user token, see Obtaining a User Token Through Password Authentication.

Request Parameters

**Table 3** Request header parameters
Parameter	Mandatory	Type	Description
Content-Type	Yes	String	Content type. The value is application/json.

**Table 4** Request body parameters
Parameter	Mandatory	Type	Description
category	Yes	String	Scenario type. The options are: popularity: popularity-based recommendations relation: associated item recommendations personalization: recommendations based on the prediction on what you may also like
datasource_id	Yes	String	Data source ID
scene_name	Yes	String	Scenario name, which can contain letters, digits, underscores (_), and hyphens (-) Minimum: 1 Maximum: 64
specs_config	Yes	SpecsConfig object	Computing specifications
schedule	No	String	Scheduling information
job_configs	Yes	jobConfig object	Job settings

**Table 5** SpecsConfig
Parameter	Mandatory	Type	Description
offline	Yes	String	Offline computing specifications
nearline	No	String	Real-time computing specifications
rank	No	String	Deep learning computing specifications
online_tps	No	Integer	Max. number of concurrent online services

**Table 6** jobConfig
Parameter	Mandatory	Type	Description
nearline_recall_param	No	NearLineRecallParam object	Parameters of a nearline retrieval job (required for nearline retrieval jobs)
max_recommended_num	No	Integer	Max. number of candidate sets (required for retrieval jobs) Minimum: 1 Maximum: 200
match_feature_pairs	No	Array of MatchFeaturePair objects	Matched feature pair (required for feature matching-based retrieval jobs)
striping	No	Striping object	Row-based strategy (required for feature matching-based retrieval job, itemCF retrieval job, and userCF retrieval job)
match_type	No	String	Matching type (required for feature matching-based retrieval jobs). The options are: UI: recommending items based on users UU: recommending users based on users II: recommending items based on items IU: recommending users based on items
matrix_factorization	No	MatrixFactorization object	Matrix decomposition parameter settings (required for the ALS-based MF jobs)
behavior_frequencys	No	Array of BehaviorFrequency objects	Behavior frequency information (required for historical behavior-based candidate set generation jobs)
file_path	No	String	File path (required for business rule - manual import retrieval jobs)
ucb_param	No	UcbParam object	UCB job parameter (required for UCB-based retrieval jobs)
behavior_gravity	No	BehaviorGravity object	Gravity decay factor (required for the comprehensive behavior popularity-based retrieval jobs)
category	No	Category object	Type (required for the comprehensive behavior popularity-based retrieval jobs)
behavior_logic	No	String	Behavior filter logic (required for historical behavior filter jobs). The options are: AND: If both conditions are met, the data is filtered. OR: If one condition is met, the data is filtered.
features_engineering	No	EtlBasicParameter object	Feature parameter (required for offline feature engineering jobs)
sample_param	No	SampleParam object	Sample parameter (required for offline feature engineering jobs)
deep_learning_parameters	No	DeepLearingParam object	General parameters of a ranking job (required by LR, DeepFM, and AutoGroup)
algorithm_specify_parameters	No	AlgorithmSpecifyParameters object	Specific parameter of a ranking algorithm (required for LR, DeepFM, and AutoGroup)
load_widetable	No	Boolean	Importing a wide table (required for offline data import jobs)
load_profile	No	Boolean	Importing a profile (required for offline data import jobs)
save_mode	No	String	Retaining a wide table (required for offline data import jobs). The options are: append: Yes new: No -Overwrite: Overwrite
indicators	No	Array of Indicator objects	Statistical indicator (required for effect evaluation jobs)
offline_rank_job_name	No	String	Name of an offline ranking job (required for online training jobs)
update_interval	No	Integer	Update interval (required for online training jobs)
optimizer	No	Optimizer object	Optimizer (required for online training jobs)
flows	No	Flow object	Online process flow (required for online training jobs)

**Table 7** NearLineRecallParam
Parameter	Mandatory	Type	Description
time_limit	No	Boolean	Time filter
timeFeature	No	String	Time feature
retainDays	No	Integer	Retention period (days)
recall_fileds	No	Array of RecallFiled objects	Retrieved field
itemCF_job_name	No	String	Name of an itemCF job

**Table 8** RecallFiled
Parameter	Mandatory	Type	Description
name	No	String	Field name
value	No	Integer	Number of used field values Minimum: 1 Maximum: 10 Default: 1

**Table 9** MatchFeaturePair
Parameter	Mandatory	Type	Description
user_feature_name	No	String	User feature
item_feature_name	No	String	Item feature
weight	No	Double	Weight
match_count	No	Boolean	Measurement of the number of matched tags

**Table 10** Striping
Parameter	Mandatory	Type	Description
nearest_neighborhood	Yes	Integer	Nearest neighbors
band	Yes	Integer	Similarity degree Minimum: 1 Maximum: 20
row	Yes	Integer	Similarity distance Minimum: 1 Maximum: 10

**Table 11** MatrixFactorization
Parameter	Mandatory	Type	Description
implicit_vector_rank	Yes	Integer	Embedding size Minimum: 1 Maximum: 100
regular_param	Yes	Double	Optimization lambda Minimum: 1.0E-8 Maximum: 1
max_iterator_num	Yes	Integer	Number of iterations Minimum: 1 Maximum: 50

**Table 12** BehaviorFrequency
Parameter	Mandatory	Type	Description
behavior_type	Yes	String	Behavior type. The options are: view indicates that you browsed an item. click indicates that you clicked an item. collect indicates that you added an item to favorites. uncollect indicates that you removed an item from favorites. search_click indicates that you searched and clicked an item. comment indicates that you made comments on an item. share indicates that you shared an item with others. like indicates that you gave an item a thumb-up. dislike indicates that you gave an item a thumb-down. grade indicates that you rated an item. consume indicates that you bought an item (primarily refers to goods). use indicates that you watched videos/listened to music/read books. download indicates that you downloaded something. -tip indicates that you gave somebody or something a reward. subscribe indicates that you followed somebody or something.
lower_limit	No	Integer	Min. times Minimum: 1
upper_limit	No	Integer	Max. times Minimum: 1
time_interval	Yes	Integer	Time range Minimum: 1

**Table 13** UcbParam
Parameter	Mandatory	Type	Description
alpha	Yes	Double	Tradeoff parameter Minimum: 0 Maximum: 1
min_used_num	Yes	Integer	Min. number of behaviors Minimum: 30 Maximum: 1000

**Table 14** BehaviorGravity
Parameter	Mandatory	Type	Description
weaken_factor	No	Double	Decay factor Minimum: 0.1 Maximum: 5
view_type	No	String	Behavior quantity counting mode. The options are: pv: page views or clicks, measuring the number of web pages visited by website users. uv: unique visitors, counting the number of individual users accessing a site within the reporting period.
algo_type	No	String	Algorithm type. The options are: normal time

**Table 15** Category
Parameter	Mandatory	Type	Description
user_meta_list	No	Array of strings	User feature
item_meta_list	No	Array of strings	Item feature

**Table 16** EtlBasicParameter
Parameter	Mandatory	Type	Description
user_features	No	Array of FeatureTransformation objects	User feature
item_features	No	Array of FeatureTransformation objects	Item feature
rank_etl_filter	No	RankETLFilter object	Filter parameter

**Table 17** FeatureTransformation
Parameter	Mandatory	Type	Description
attr	No	Attribute object	Feature
discrete_method	No	String	Discrete method. The options are: equal_distance_discrete indicates equal-distance discretization. user_define_discrete indicates custom discrete distance. -normalize indicates normalization. null indicates non-discretization.
params	No	Object	Specific processing parameter

**Table 18** Attribute
Parameter	Mandatory	Type	Description
name	Yes	String	Name
data_type	No	String	Data type
other_uses	No	Array of strings	Other usage

**Table 19** RankETLFilter
Parameter	Mandatory	Type	Description
filter_type	Yes	String	Behavior deduplication mode. The options are: abs_weight indicates the absolute weight value. date indicates the date.
time_type	Yes	String	Time type. The options are: Day Week Month
is_monday_first	No	Boolean	Whether Monday is the first day

**Table 20** SampleParam
Parameter	Mandatory	Type	Description
divide_type	Yes	String	Division mode of training and test sets. The options are: TIME indicates the time ratio. RAMDOM indicates the number ratio.
train_rate	No	Double	Training data ratio Minimum: 0.01 Maximum: 1
test_rate	No	Double	Test data ratio Minimum: 0.01 Maximum: 1

**Table 21** DeepLearingParam
Parameter	Mandatory	Type	Description
initial_parameters	No	Initial object	Initialization parameter
optimize_parameters	No	Optimizer object	Optimization parameter
regular_parameters	No	Regular object	Lambda parameter
max_iterations	No	Integer	Max. iterations Minimum: 1 Maximum: 1000
early_stop_iterations	No	Integer	Iterations at early stopping Minimum: 1 Maximum: 1000
batch_size	No	Integer	Batch size Minimum: 1
dataset_split_parts	No	Integer	Number of training datasets to be split Minimum: 1 Maximum: 10
restart_train	No	Boolean	Retraining

**Table 22** Initial
Parameter	Mandatory	Type	Description
initial_method	Yes	String	Initialization method Enumeration values: normal uniform xavier
mean_value	No	Double	Mean Minimum: -1 Maximum: 1
standard_deviation	No	Double	Standard deviation Minimum: 0 Maximum: 1
min_value	No	Double	Min. value Minimum: -1 Maximum: 0
max_value	No	Double	Max. value Minimum: 0 Maximum: 1

**Table 23** Regular
Parameter	Mandatory	Type	Description
l2_regularization	No	Double	Lambda 2 Minimum: 0 Maximum: 1
regular_loss_compute_mode	No	String	Regular loss calculation mode Enumeration values: full batch
embed_l2_regularization	No	Double	Lambda 2 of embedding size Minimum: 0 Maximum: 1
wide_l2_regularization	No	Double	Lambda 2 of the wide part Minimum: 0 Maximum: 1
structure_l2_regularization	No	Double	Lambda 2 of the structured part Minimum: 0 Maximum: 1

**Table 24** AlgorithmSpecifyParameters
Parameter	Mandatory	Type	Description
latent_vector_length	No	Integer	Embedding size (required for DeepFM) Minimum: 1 Maximum: 100
architecture	No	Array of integers	Neural network structure (required for DeepFM)
active_function	No	String	Activation function (required for DeepFM and AutoGroup) Enumeration values: relu sigmoid tanh
value_keep_probability	No	Double	Neuron retention probability (required for DeepFM and AutoGroup) Minimum: 0 Maximum: 1
embed_size	No	Array of integers	Embedding size of each degree (required for AutoGroup)
mlp_architecture	No	Array of integers	Neural network structure (required for AutoGroup)
max_order	No	Integer	Max. interactions (required for AutoGroup)
hash_sizes	No	Array of integers	Hash length (required for AutoGroup)
hash_compensation	No	Array of numbers	Feature interaction penalty coefficient (required for AutoGroup)
use_wide_part	No	Boolean	Wide part required (required for AutoGroup)
structure_optimizer	No	Optimizer object	Optimizer parameter (required for AutoGroup)
merge_multi_hot	No	Boolean	Merge multi-value feature (required for AutoGroup)
fix_structure	No	Boolean	Fix hash structure (required for AutoGroup)

**Table 25** Indicator
Parameter	Mandatory	Type	Description
indicator_name	No	String	Indicator. The options are: PV UV Custom
indicator_params	No	IndicatorParam object	Indicator parameter (required for custom metric)

**Table 26** IndicatorParam
Parameter	Mandatory	Type	Description
customize_parameter	No	CustomizeParameter object	Custom parameter
customize_formula	No	CustomizeFormula object	Custom formula

**Table 27** CustomizeParameter
Parameter	Mandatory	Type	Description
alias	Yes	String	Alias
behavior_type	Yes	String	Behavior type
threshold	No	Double	Threshold Minimum: 0 Maximum: 1
deduplication	Yes	String	Deduplication

**Table 28** CustomizeFormula
Parameter	Mandatory	Type	Description
alias	No	String	Alias
formula	No	String	Formula

**Table 29** Optimizer
Parameter	Mandatory	Type	Description
type	No	String	Optimizer type Enumeration values: adam adagrad ftrl
learning_rate	No	Integer	Learning rate Minimum: 0 Maximum: 1
initial_accumulator_value	No	Double	Initial gradient sum Minimum: 0 Maximum: 1
lambda1	No	Double	Lambda 1 Minimum: 0 Maximum: 1
lambda2	No	Double	Lambda 2 Minimum: 0 Maximum: 1
epsilon	No	Double	Epsilon Minimum: 0 Maximum: 1
decay_rate	No	Double	Decay factor Minimum: 0 Maximum: 1
decay_steps	No	Double	Decay step Minimum: 1

**Table 30** Flow
Parameter	Mandatory	Type	Description
flow_id	Yes	String	Process flow ID
attr_pair_rules_filter	No	Array of AttrPairRules objects	Feature pair filter
attr_pair_rules_reserve	No	Array of AttrPairRules objects	Feature pair to be reserved
deduplication_list	No	Array of Deduplication objects	Feature deduplication
attribute_info	No	AttributeInfo object	Comprehensive ranking information
bloom_filter_conf	No	BloomFilterConf object	Bloom filter settings
group_attr	No	String	The scatter attribute for grouping
pre_deal	No	Boolean	Deduplication before ranking
rank_setting	No	String	Ranking configuration information
rules	No	Rule object	Candidate set merging
filter_sets	No	Array of strings	Filter configuration information
attr_value_rules_filter	No	Array of AttrValueRules objects	Feature filter
attr_value_rules_reserve	No	Array of AttrValueRules objects	Feature to be reserved
ctr_job	No	String	Ranking job (required when click-through rate is used)
ratio	No	Integer	Traffic proportion Minimum: 1 Maximum: 100
toppings	No	Array of strings	List of candidate sets to be pinned on top

**Table 31** AttrPairRules
Parameter	Mandatory	Type	Description
attr_pairs	No	Array of AttrPair objects	Feature pair

**Table 32** AttrPair
Parameter	Mandatory	Type	Description
party_a	No	String	Feature name of the recommended item
party_b	No	String	Feature name of the recommended item

**Table 33** Deduplication
Parameter	Mandatory	Type	Description
attributes	No	Array of strings	Feature

**Table 34** AttributeInfo
Parameter	Mandatory	Type	Description
rank_feature_pairs	No	Array of RankFeaturePair objects	Matched feature pair
numerical_attrs	No	Array of NumericalAttr objects	Feature weight
num_statistics_type	No	String	Statistics mode. The options are: ORDER indicates that weights are accumulated based on the feature value sequence. ABS indicates that weights are accumulated based on the absolute value. Enumeration values: ORDER ABS

**Table 35** RankFeaturePair
Parameter	Mandatory	Type	Description
feature_name_a	No	String	Feature of the item to be recommended
feature_name_b	No	String	Feature of the recommended item
weight	No	Float	Weight Minimum: 0.01 Maximum: 1

**Table 36** NumericalAttr
Parameter	Mandatory	Type	Description
name	Yes	String	Feature name
weight	Yes	Float	Weight Minimum: 0.001 Maximum: 1

**Table 37** BloomFilterConf
Parameter	Mandatory	Type	Description
behaviors	No	Array of strings	Type of the behavior to be filtered
interval	No	Integer	Filter time Minimum: 1 Maximum: 7

**Table 38** Rule
Parameter	Mandatory	Type	Description
table_name	Yes	String	Table name of a candidate set
rule_ratio	Yes	Integer	Rule ratio Minimum: 1 Maximum: 100
priority	Yes	Integer	Priority Minimum: 1 Maximum: 10

**Table 39** AttrValueRules
Parameter	Mandatory	Type	Description
attr_values_a	No	Array of AttrValue objects	Feature value settings of the recommended item
attr_values_b	Yes	Array of AttrValue objects	Feature value settings of the item to be recommended

**Table 40** AttrValue
Parameter	Mandatory	Type	Description
name	Yes	String	Feature name
value	Yes	String	Feature value

Response Parameters

Status code: 200

**Table 41** Response body parameters
Parameter	Type	Description
is_success	Boolean	Whether the request is successful
message	String	Response message (This field is not returned when the request is successful.)
error_code	String	Error code (This parameter is not returned when the request is successful.)
scene	scene object	Scenario

**Table 42** scene
Parameter	Type	Description
category	String	Type
type	String	Scenario type
scene_name	String	Scenario name
scene_id	String	Scenario ID
datasource_id	String	Data source ID
status	String	Status
created_at	String	Creation time
update_at	String	Update time
workspace_id	String	Workspace ID
service_type	String	Service type

Example Requests

This API is used to create a scenario.

/v2.0/testuuidxxxxxxxxxxxxxxxxxxxxxxxx/workspaces/testuuidxxxxxxxxxxxxxxxxxxxxxxxx/intelligent-scenes

{
  "category" : "popularity",
  "job_configs" : { },
  "schedule" : "00 50 01 * * ?",
  "specs_config" : {
    "online_tps" : 5,
    "offline" : "4CU",
    "nearline" : "2CU",
    "rank" : "8CU"
  },
  "description" : "",
  "datasource_id" : "aa6d657026de42a2927a50400ae69a4b",
  "scene_name" : "ceshi3"
}

Example Responses

Status code: 200

{
  "scene" : {
    "type" : "UI",
    "service_type" : "rec",
    "scene_name" : "ceshi3",
    "category" : "popularity",
    "scene_id" : "ae1d4f1ee659404eaefb7a3a3f1c716f",
    "datasource_id" : "aa6d657026de42a2927a50400ae69a4b",
    "status" : "Draft",
    "created_at" : 1588857123744,
    "update_at" : 0,
    "schedule" : "00 50 01 * * ?",
    "next_schedule_time" : 1588873800000,
    "workspace_id" : "06a7c49afc00d4972ff1c0113d8c49ba",
    "description" : ""
  },
  "is_success" : true
}

Status Codes

Status Code	Description
200	OK

Error Codes

See Error Codes.

Parent topic: Scenario

Last Article: Creating a Custom Scenario

Next Article: Querying the Details of a Scenario

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