otto-de/MultiTRON
🤹 MultiTRON: Pareto Front Approximation for Multi-Objective Session-Based Recommender Systems, accepted at ACM RecSys 2024.
MultiTRON helps e-commerce managers and recommendation system strategists improve online shopping experiences by optimizing multiple business goals at once. It takes historical user session data and outputs refined recommendation models that balance competing objectives like increasing clicks and boosting purchases. This is for professionals managing online stores, streaming platforms, or any service offering personalized product or content recommendations.
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Use this if you need to optimize your recommendation engine to balance multiple, often conflicting, business objectives such as maximizing user engagement (clicks) and conversion rates (purchases) simultaneously.
Not ideal if your recommendation system has only a single, straightforward objective, or if you do not have the technical expertise to implement a machine learning model.
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Language
Python
License
MIT
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Last pushed
Aug 04, 2025
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