@article{Potter_Liu_Lala_Loanzon_Sun_2022, title={GRU4RecBE: A Hybrid Session-Based Movie Recommendation System (Student Abstract)}, volume={36}, url={https://ojs.aaai.org/index.php/AAAI/article/view/21651}, DOI={10.1609/aaai.v36i11.21651}, abstractNote={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.}, number={11}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Potter, Michael and Liu, Hamlin and Lala, Yash and Loanzon, Christian and Sun, Yizhou}, year={2022}, month={Jun.}, pages={13029-13030} }