56 citations · 163 across the 10 of their papers we have counts for
5 papers · 1 filter
Beyond Personalization: Social Content Recommendation for Creator Equality and Consumer Satisfaction
Wenyi Xiao, Huan Zhao, Haojie Pan +3
An effective content recommendation in modern social media platforms should benefit both creators to bring genuine benefits to them and consumers to help them get really interestin…
Behavior Sequence Transformer for E-commerce Recommendation in Alibaba
Qiwei Chen, Huan Zhao, Wei Li +2
Deep learning based methods have been widely used in industrial recommendation systems (RSs). Previous works adopt an Embedding&MLP paradigm: raw features are embedded into low-dim…
Multi-Interest Network with Dynamic Routing for Recommendation at Tmall
Chao Li, Zhiyuan Liu, Mengmeng Wu +7
Industrial recommender systems usually consist of the matching stage and the ranking stage, in order to handle the billion-scale of users and items. The matching stage retrieves ca…
Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba
Jizhe Wang, Pipei Huang, Huan Zhao +3
Recommender systems (RSs) have been the most important technology for increasing the business in Taobao, the largest online consumer-to-consumer (C2C) platform in China. The billio…
Side Information Fusion for Recommender Systems over Heterogeneous Information Network
Huan Zhao, Quanming Yao, Yangqiu Song +2
Collaborative filtering (CF) has been one of the most important and popular recommendation methods, which aims at predicting users' preferences (ratings) based on their past behavi…