Learned Ranking Function: From Short-term Behavior Predictions to Long-term User Satisfaction
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arXiv
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| Hauptverfasser: | , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866913466775764992 |
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| author | Wu, Yi Chang, Daryl She, Jennifer Zhao, Zhe Wei, Li Heldt, Lukasz |
| author_facet | Wu, Yi Chang, Daryl She, Jennifer Zhao, Zhe Wei, Li Heldt, Lukasz |
| contents | We present the Learned Ranking Function (LRF), a system that takes short-term user-item behavior predictions as input and outputs a slate of recommendations that directly optimizes for long-term user satisfaction. Most previous work is based on optimizing the hyperparameters of a heuristic function. We propose to model the problem directly as a slate optimization problem with the objective of maximizing long-term user satisfaction. We also develop a novel constraint optimization algorithm that stabilizes objective trade-offs for multi-objective optimization. We evaluate our approach with live experiments and describe its deployment on YouTube. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_06512 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Learned Ranking Function: From Short-term Behavior Predictions to Long-term User Satisfaction Wu, Yi Chang, Daryl She, Jennifer Zhao, Zhe Wei, Li Heldt, Lukasz Machine Learning Artificial Intelligence Information Retrieval We present the Learned Ranking Function (LRF), a system that takes short-term user-item behavior predictions as input and outputs a slate of recommendations that directly optimizes for long-term user satisfaction. Most previous work is based on optimizing the hyperparameters of a heuristic function. We propose to model the problem directly as a slate optimization problem with the objective of maximizing long-term user satisfaction. We also develop a novel constraint optimization algorithm that stabilizes objective trade-offs for multi-objective optimization. We evaluate our approach with live experiments and describe its deployment on YouTube. |
| title | Learned Ranking Function: From Short-term Behavior Predictions to Long-term User Satisfaction |
| topic | Machine Learning Artificial Intelligence Information Retrieval |
| url | https://arxiv.org/abs/2408.06512 |