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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 / No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

GRU4RecBE: A Hybrid Session-Based Movie Recommendation System (Student Abstract)

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Authors

Michael Potter

University of California Los Angeles


Hamlin Liu

University of California Los Angeles


Yash Lala

University of California Los Angeles


Christian Loanzon

University of California Los Angeles


Yizhou Sun

University of California Los Angeles


DOI:

10.1609/aaai.v36i11.21651


Abstract:

We present a novel movie recommendation system, GRU4RecBE, which extends the GRU4Rec architecture with rich item features extracted by the pre-trained BERT model. GRU4RecBE outperforms state-of-the-art session-based models over the benchmark MovieLens 1m and MovieLens 20m datasets.