AAAI2022
GRU4RecBE: A Hybrid Session-Based Movie Recommendation System (Student Abstract)
Michael Potter, Hamlin Liu, Yash Lala, Christian Loanzon, Yizhou Sun
被引用 8 次
摘要
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.