213 citations · 577 across the 11 of their papers we have counts for
11 papers
ContentCTR: Frame-level Live Streaming Click-Through Rate Prediction with Multimodal Transformer
Jiaxin Deng, Dong Shen, Shiyao Wang +4
In recent years, live streaming platforms have gained immense popularity as they allow users to broadcast their videos and interact in real-time with hosts and peers. Due to the dy…
Instant Representation Learning for Recommendation over Large Dynamic Graphs
Cheng Wu, Chaokun Wang, Jingcao Xu +7
Recommender systems are able to learn user preferences based on user and item representations via their historical behaviors. To improve representation learning, recent recommendat…
Multi-behavior Self-supervised Learning for Recommendation
Jingcao Xu, Chaokun Wang, Cheng Wu +6
Modern recommender systems often deal with a variety of user interactions, e.g., click, forward, purchase, etc., which requires the underlying recommender engines to fully understa…
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…
Image Matters: Visually modeling user behaviors using Advanced Model Server
Tiezheng Ge, Liqin Zhao, Guorui Zhou +13
In Taobao, the largest e-commerce platform in China, billions of items are provided and typically displayed with their images. For better user experience and business effectiveness…
Rocket Launching: A Universal and Efficient Framework for Training Well-performing Light Net
Guorui Zhou, Ying Fan, Runpeng Cui +3
Models applied on real time response task, like click-through rate (CTR) prediction model, require high accuracy and rigorous response time. Therefore, top-performing deep models o…
Deep Interest Network for Click-Through Rate Prediction
Guorui Zhou, Chengru Song, Xiaoqiang Zhu +7
Click-through rate prediction is an essential task in industrial applications, such as online advertising. Recently deep learning based models have been proposed, which follow a si…
Hierarchical Latent Semantic Mapping for Automated Topic Generation
Guorui Zhou, Guang Chen
Much of information sits in an unprecedented amount of text data. Managing allocation of these large scale text data is an important problem for many areas. Topic modeling performs…