DeepFM is a popular click-through-rate (CTR) model developed by Huawei's Noah's Ark Lab. In this project, we modifies the original neural network structure for better CTR predictions. More specifically, we a. introduced pooling layers to better capture the higher order feature interactions and b. added a linear layer to assign weights to the constituent deep model and factorisation machine (FM) model when combining the outputs. Our experimental results show that both extensions are able to improve the accuracy of the original DeepFM model.

Image credit: videomaker.simpleshow.com