Chenghuan Guo

Sep 30, 2024 | amazon.science | Jin Shang |Chenghuan Guo |Minghao Sun |Yan Gao

In e-commerce recommender systems, providing product suggestions to customers that are often bought together, which is called “complementary recommendation,” not only improves customer experience but also boosts business impact. However, in practice, it is highly challenging to efficiently extract the complementary relations between the items due to noisy and low coverage of the co-purchased records in transaction datasets.