AutoAttention: Automatic Field Pair Selection for Attention in User Behavior Modeling

no code implementations • 27 Oct 2022 • Zuowu Zheng, Xiaofeng Gao, Junwei Pan, Qi Luo, Guihai Chen, Dapeng Liu, Jie Jiang

In this paper, we propose a novel model named AutoAttention, which includes all item/user/context side fields as the query, and assigns a learnable weight for each field pair between behavior fields and query fields.

Click-Through Rate Prediction

HIEN: Hierarchical Intention Embedding Network for Click-Through Rate Prediction

no code implementations • 1 Jun 2022 • Zuowu Zheng, Changwang Zhang, Xiaofeng Gao, Guihai Chen

Based on this observation, in this paper, we propose a novel approach Hierarchical Intention Embedding Network (HIEN), which considers dependencies of attributes based on bottom-up tree aggregation in the constructed attribute graph.

Attribute Click-Through Rate Prediction +1