Dual-attentional Factorization-Machines based Neural Network for User Response Prediction.
2020
This paper proposes Dual-attentional Factorization-Machines (DFM), which incorporates global-wise attention and element-wise attention with FM for user response prediction. We further extend DFM with a deep neural network and name this new model Dual-attentional Factorization-machines based Network (DFNet). Comprehensive experiments are conducted on two real-world datasets to demonstrate the effectiveness of DFM and DFNet over the state-of-the-art models for user response prediction.
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