AiTEMS overview
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    AiTEMS overview

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    Article Summary

    Available in Classic and VPC

    AiTEMS is a service that can quickly and easily provide and implement a recommendation service tailored to the user's taste without requiring expertise in machine learning (ML) and AI. With using AiTEMS, the verified personalized recommendation service used by NAVER Shopping can be applied to customer services, and customized services can be provided for each user according to the user's taste and behavioral pattern in line with service trends in the AI era.


    AiTEMS provides services for the purpose of conducting and testing dataset learning. The learned results can be applied to customer's services through API.

    Various features provided by AiTEMS

    A variety of features offered by AiTEMS is as follows.

    • Personalized recommendation service: responds to changes in user behavior patterns by matching user’s information (purchase history, etc.) with product information, and recommends products that suit the user's taste. Recommendation service can be applied even when information is insufficient, such as new users or new products. Arrange products according to rankings customized for each user to enhance the probability of purchase or use by users.
    • Fully managed type service: this service contains all the recommendation technologies necessary for machine learning, such as data preprocessing, learning, tuning, and prediction. It learns based on the uploaded dataset and provides recommendation results.
    • Reduced establishment and operation costs: AiTEMS can reduce the time and cost of building a service and introducing a system yourself. Reduce unnecessary costs by using only when you need it and paying only for what you use.
    • Strong data security: the data uploaded for learning and learning results are owned by the service provider. All data is encrypted and stored and used only to provide recommendations, enabling strong data security.
    • Hyperparameter Optimization (HPO) settings: improve the prediction accuracy of machine learning models and implement optimal machine learning models through HPO settings

    Utilization of AiTEMS

    You can apply AiTEMS to various places to provide recommendation services. Typically, a personalization feature can be implemented and provided in a shopping mall such as NAVER Shopping.
    Different users may prefer different styles even if they want the same product, one piece, as follows. AiTEMS analyzes the history of user's activity and preference, rearranges and provides recommended products based on a personalization model, and allows users to purchase products that suit their taste.

    Information on AiTEMS user guide

    AiTEMS provides services in the Korea Region. See the following table of contents and their details for best use of AiTEMS.

    • AiTEMS overview: introduction to AiTEMS and related resources helpful for the use
    • Prerequisites for using AiTEMS: supported specifications for using AiTEMS and pricing information
    • AiTEMS scenario: introduction to the full process for using AiTEMS
    • Get started: how to start using AiTEMS
    • Using AiTEMS: guide on how to use the features provided by AiTEMS
      • Service: guide on the screen composition of the Service menu and how to use the feature
      • Dataset: guide on the screen composition of the Dataset menu and how to use the feature
      • Schema: guide on the screen composition of the Schema menu and how to use the feature
      • Usage: Guidance on screen configuration of the Usage menu and how to view service usage status
    • Managing AiTEMS permissions: how to manage AiTEMS Authorization using Sub Account
    • AiTEMS glossary: a guide to key terms and explanations you must know when using AiTEMS
    • AiTEMS release notes: update history of the AiTEMS user guide

    NAVER Cloud Platform provides various related resources as well as the guide to help customers better understand AiTEMS. If you're a developer or marketer in need of detailed information while you're considering adopting AiTEMS for your company or establishing data related policies, then please make good use of the resources below.

    • Improvement in comprehension and usage methods for AiTEMS
    • Guides for integrated services required for the use of AiTEMS
      • Object Storage: how to use Object Storage that can store dataset files and learning results required for learning
      • Sub Account user guide: how to use a Sub Account to help manage AiTEMS operations

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