Features Features

  • Elastic Scaling

    Dynamically adjusts computing capabilities and bandwidth to efficiently meet service requirements and reduce costs.

  • Leading Technologies

    Tags the recommended items using the visual and NLP technologies and identifies user preferences based on user behaviors.

  • Extensive Algorithms

    Incorporates collaborative filtering, CTR estimation, graph and deep learning algorithms to help improve ease of use and recommendation accuracy.

  • Real-Time Recommendations

    Responds to recommendation requests in milliseconds, adjusts recommendation lists in seconds, and updates candidate sets in minutes.

Business Challenges Business Challenges

  • Information Overload

    Because of the massive amounts of data generated on the Internet, website users struggle to quickly and accurately locate content or products of interest, severely hindering user experience and loyalty.

  • Neglect of Long Tail Effect

    Only mainstream content and products are recommended. As a result, opportunities for other excellent but less famous content or products are limited and are unlikely to be discovered by users.

  • Difficult Content Analysis and Mining

    In the 5G era, it is unlikely that manpower can analyze the growing amounts of information generated on the Internet. Although AI technologies are of great help, they are not easy to understand or master.

  • Points of Interest Reduced

    Recommendations based on historical user behaviors can meet users' interests only in the short term. More proactive recommendations are required to stimulate and diversify users' points of interest.

Practices Practices

Content Recommendations E-commerce Recommendations
Content Recommendations

Content Recommendations

Helps users find interesting and valuable content from a massive amount of information.


    Content Controllable Identifying unqualified content is key for UGC websites. AI technologies are used to identify violations and reduce operation risks.

    Tagging Content Identifies content scenarios, characters, voice, and text to classify tags in a hierarchical form.

    Identifying User Preferences Analyzes user preferences based on user behaviors.

E-commerce Recommendations

E-commerce Recommendations

Estimates product similarity based on users' purchased products and updates candidate lists in real time, improving user experience.


    Easy to Use Provides templates (that define data input formats, algorithms, and process) to simplify the configuration process.

    Elastic Scaling Supports high concurrency and second-level expansion of computing capabilities.

Solution Architectures Solution Architectures

Content Recommendations E-commerce Recommendations
Content Recommendations
E-commerce Recommendations

Technical Advantages Technical Advantages

  • AI Technologies

    AI technologies are used to audit content, tag items, and personalize precision matching and sorting.

  • Real-Time Big Data Analysis

    The Huawei Cloud big data platform updates users' interest information in real time based on second-level user behavior analysis.

  • Service HA

    The Huawei Cloud UPredict platform supports ABTest, brings algorithm models online with just one click, and provides high concurrency, second-level scaling, and high-reliability services.

Partner Cases Partner Cases