GRU4RecBE: A Hybrid Session-Based Movie Recommendation System (Student Abstract)
Keywords:Session-Based Recommendation, Bidirectional Encoder Representations From Transformers, Gated Recurrent Unit, Movie Recommendations, Ranking
AbstractWe 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.
How to Cite
Potter, M., Liu, H., Lala, Y., Loanzon, C., & Sun, Y. (2022). GRU4RecBE: A Hybrid Session-Based Movie Recommendation System (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13029-13030. https://doi.org/10.1609/aaai.v36i11.21651
AAAI Student Abstract and Poster Program