132 citations · 768 across the 36 of their papers we have counts for
8 papers · 1 filter
Mutual Harmony: Sequential Recommendation with Dual Contrastive Network
Guanyu Lin, Chen Gao, Yinfeng Li +6
With the outbreak of today's streaming data, the sequential recommendation is a promising solution to achieve time-aware personalized modeling. It aims to infer the next interacted…
Practitioners Versus Users: A Value-Sensitive Evaluation of Current Industrial Recommender System Design
Zhilong Chen, Jinghua Piao, Xiaochong Lan +4
Recommender systems are playing an increasingly important role in alleviating information overload and supporting users' various needs, e.g., consumption, socialization, and entert…
DisenHCN: Disentangled Hypergraph Convolutional Networks for Spatiotemporal Activity Prediction
Yinfeng Li, Chen Gao, Quanming Yao +3
Spatiotemporal activity prediction, aiming to predict user activities at a specific location and time, is crucial for applications like urban planning and mobile advertising. Exist…
DVR: Micro-Video Recommendation Optimizing Watch-Time-Gain under Duration Bias
Yu Zheng, Chen Gao, Jingtao Ding +4
Recommender systems are prone to be misled by biases in the data. Models trained with biased data fail to capture the real interests of users, thus it is critical to alleviate the…
Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation
Chang Meng, Ziqi Zhao, Wei Guo +6
Multi-types of behaviors (e.g., clicking, adding to cart, purchasing, etc.) widely exist in most real-world recommendation scenarios, which are beneficial to learn users' multi-fac…
Causal Inference in Recommender Systems: A Survey and Future Directions
Chen Gao, Yu Zheng, Wenjie Wang +3
Recommender systems have become crucial in information filtering nowadays. Existing recommender systems extract user preferences based on the correlation in data, such as behaviora…