213 citations · 342 across the 3 of their papers we have counts for
4 papers
Res-embedding for Deep Learning Based Click-Through Rate Prediction Modeling
Guorui Zhou, Kailun Wu, Weijie Bian +3
Recently, click-through rate (CTR) prediction models have evolved from shallow methods to deep neural networks. Most deep CTR models follow an Embedding\&MLP paradigm, that is, fir…
Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction
Qi Pi, Weijie Bian, Guorui Zhou +2
Click-through rate (CTR) prediction is critical for industrial applications such as recommender system and online advertising. Practically, it plays an important role for CTR model…
Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction
Kan Ren, Jiarui Qin, Yuchen Fang +8
User response prediction, which models the user preference w.r.t. the presented items, plays a key role in online services. With two-decade rapid development, nowadays the cumulate…
Deep Interest Evolution Network for Click-Through Rate Prediction
Guorui Zhou, Na Mou, Ying Fan +5
Click-through rate~(CTR) prediction, whose goal is to estimate the probability of the user clicks, has become one of the core tasks in advertising systems. For CTR prediction model…