Description
We explore potential extensions to one of the state-of-the-art recommender systems named FiBiNET which assigns importance to feature embeddings.
Combining feature importance and bilinear feature interaction for click-through rate prediction.
We explore potential extensions to one of the state-of-the-art recommender systems named FiBiNET which assigns importance to feature embeddings.