Learning management

Available in Classic and VPC

Learning management describes how to connect a dataset to be learned on to the service, how to proceed with learning, how to test completed learning results, and how to change cycle learning settings.

Connect dataset

To proceed with learning, you need to connect a dataset to the service.

The following describes how to connect a dataset.

1. Click the environment you are using in the Region menu and Platform menu of the NAVER Cloud Platform console.
2. Click the Services > AI Services > AiTEMS menus in that order.
3. Click the Service menu.
4. Click the service to connect the dataset to from the list of services.
5. Click the [Dataset management] button in Dataset information.
6. When the Dataset management pop-up window appears, select a dataset to connect from the drop-down menu for each item.
7. Click the [OK] button.
   • Connected dataset information is displayed in Dataset information, and the [Learning management] button is activated.

Proceed with learning

The following describes how to proceed with dataset learning.

1. Click the environment you are using in the Region menu and Platform menu of the NAVER Cloud Platform console.
2. Click the Services > AI Services > AiTEMS menus in that order.
3. Click the Service menu.
4. Click the desired service to proceed with learning from the list of services.
5. Click the [Learning management] button.
   • The [Learning management] button is enabled only when a dataset is connected to the service. If the button is disabled, connect the dataset first.
6. When the learning management pop-up window appears, set the learning information and click the [Start learning] button.

   • Recommendation types: select a referral type

     • Personalized recommendation: based on past history, it provides data on recommended items that each individual might like
     • Related item recommendation: based on the item's related history, it provides recommended item data that each individual might like
     • Popular item recommendation: provides data of popular recommended items by ranking

   • Set HPO: set options related to model creation

     • If HPO (Hyperparameter Optimization) is not set, it learns using the optimized algorithm inside AiTEMS. Set the HPO to achieve the optimal learning model.
     Note

     The Popular item recommendation type requires HPO to be set, and the group_column and max_group_recommend_top options can only be set when the Popular item recommendation type is selected. The details on setting HPO parameters for each recommendation type are as follows.

     Recommendation types	Parameter name	Description	Default value	Available range
     Personalized recommendation and related item recommendation	session_max_timestamp	Maximum idle time between actions to be regarded as the same sessions (second)	1800 (30 minutes)	5 or more
     	item_top_n	The maximum number of products to be used for recommendation, used in order of popularity	20,000	1,000~500,000
     	min_item_cut	The minimum number of conditions for appearing	5	1 or more
     	min_session_length	The minimum number of actions within a session	2	2 or more
     	max_user_recommend_top	The maximum number of recommended products per user	100	1~1,000
     	max_relate_recommend_top	The maximum number of related recommended products per product	100	1~1,000
     	remove_history_item	Removal status of a product that already has a history of recommending personalized products	False	-
     Popular item recommendation	group_column	List of group columns extracted by popularity	-	-
     	target_column	Target columns to be extracted by popularity	-	-
     	max_group_recommend_top	The maximum number of popular products per group	100	1~1,000

   • Learning description: enter the description of learning

7. From the notification pop-up window, click the [OK] button.
   • The learning progress can be checked in the status of learning information.

Test learning results

You can test the results to see if the dataset has been trained correctly.
The following describes how to conduct a test.

1. Click the environment you are using in the Region menu and Platform menu of the NAVER Cloud Platform console.
2. Click the Services > AI Services > AiTEMS menus in that order.
3. Click the Service menu.
4. Click the desired service to test results from the list of services.
5. Click the [Test recommendation results] button.
6. When the pop-up window to test recommendation results appears, select the learning you want to test.
7. Enter the required information according to the learning you've chosen.
   • Target ID: if you are testing personalized or related recommendation results, enter the following information
     • Personalized recommendation: enter USER_ID to look up in learning results
     • Related items recommendation: enter the ITEM_ID to look up in the learning results
   • Column: if you are testing popular item recommendation results, enter data to look up in learning results.
8. Click the [Search] button.
   • You can check the test results in Results at the bottom of the pop-up window.

Change settings of cyclic learning

Cyclic learning allows you to modify the interval at which data is updated, and you can stop or restart learning by changing the learning settings state.

Edit update interval

The update interval defaults to 12 hours, and you can edit the update interval to 1/3/6/12 hours.
The following describes how to edit update interval.

1. Click the environment you are using in the Region menu and Platform menu of the NAVER Cloud Platform console.
2. Click the Services > AI Services > AiTEMS menus in that order.
3. Click the Service menu.
4. Click the desired service to edit update interval from the list of services.
5. Click the [Edit] button for update interval.
6. After selecting the desired update interval to edit, click the [Edit] button.

Change learning settings state

If learning is in progress, you can stop learning by changing it to Unset, and if learning is stopped, you can change it to Set to continue learning.

The following describes how to change the learning settings status.

1. Click the environment you are using in the Region menu and Platform menu of the NAVER Cloud Platform console.
2. Click the Services > AI Services > AiTEMS menus in that order.
3. Click the Service menu.
4. Click the desired service to change learning settings status from the list of services.
5. Click or of learning settings status
   • indicates unset state, click to change to set state.
   • indicates set state, click to change to unset state.
6. If you change the setting status from Unset to Set, when the pop-up window for learning management appears, set the learning information to proceed and click the [Start learning] button.
   • For more information on setting learning information, see Proceed with learning.
   • The learning settings state changes to Set, and cyclic learning proceeds again.
7. If you change the setting status from Set to Unset, check the contents of the notification pop-up window and click the [OK] button.
   • The learning setting status is changed to Unset, and cyclic learning is stopped.