xuetf/KDD_CUP_2020_Debiasing_Rush
Solution to the Debiasing Track of KDD CUP 2020
This project provides a solution for improving recommendation systems by reducing bias. It takes in user clickstream data and item features, then generates a refined list of recommended items. E-commerce managers, content platform strategists, or anyone managing a recommendation engine would use this to ensure a fairer and more diverse user experience.
160 stars. No commits in the last 6 months.
Use this if your recommendation system suffers from popularity bias, where only frequently clicked items are suggested, neglecting valuable, less-exposed content.
Not ideal if you're looking for a simple plug-and-play recommendation system without custom data processing or if your data isn't in a clickstream format.
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Last pushed
Mar 24, 2023
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