Alibaba E-Commerce AI Challenge

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  • Introduction
  • Track 1

    User Behavior Diversities Prediction

    • Description

      If embedding users and items into a heterogeneous graph, user-to-item behaviors could be treated as directed edges and item-to-item similarities could be encoded into the graph. Then recommendation task could be transformed as the graph link prediction problem. Such transition may bring a new view of recommendation system and further trigger novel algorithms to solve the bottleneck of behavior prediction problem.

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    Track 2

    Efficient User Interests Retrieval

    • Description

      In recent years, a lot of efforts have been made both in academy and industry to promote user preference prediction accuracy. However, large-scale recommender system has to trade-off between model effectiveness and efficiency as the response time limit. Our competition focuses on this problem, i.e., how to retrieve the top-k items for each user and avoid the exhausted calculation at the same time, which is very important and challenging.

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  • Agenda
  • Registration
    Jun 12, 2019 - Aug 13, 2019
    The Qualification
    Jul 5, 2019 - Aug 15, 2019
    The Semi-Finals
    Aug 22, 2019 - Sep 25, 2019
    The Finals
    Sep, 2019
  • Award
  • First Prize
    Track 1 (one team): $10,000 USD
    Track 2 (one team): $10,000 USD
    Second Prize
    Track 1 (two teams): $5,000 USD for each
    Track 2 (two teams): $5,000 USD for each
    Third Prize
    Track 1 (two teams): $2,500 USD for each
    Track 2 (two teams): $2,500 USD for each