We motivate the need for recommendation systems that can cater to the members' in-the-moment intent by leveraging their interactions from the current session. We provide an overview of an end-to-end in-session adaptive recommendations system in the context of Netflix Search. We discuss the challenges and potential solutions when developing such a system at production scale.
CITATION STYLE
Bhattacharya, M., & Lamkhede, S. (2022). Augmenting Netflix Search with In-Session Adapted Recommendations. In RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems (pp. 542–545). Association for Computing Machinery, Inc. https://doi.org/10.1145/3523227.3547407
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