437 citations · 451 across the 4 of their papers we have counts for
5 papers · 1 filter
Graph Convolutional Neural Networks for Web-Scale Recommender Systems
Rex Ying, Ruining He, Kaifeng Chen +3
Recent advancements in deep neural networks for graph-structured data have led to state-of-the-art performance on recommender system benchmarks. However, making these methods pract…
SPMC: Socially-Aware Personalized Markov Chains for Sparse Sequential Recommendation
Chenwei Cai, Ruining He, Julian McAuley
Dealing with sparse, long-tailed datasets, and cold-start problems is always a challenge for recommender systems. These issues can partly be dealt with by making predictions not in…
Translation-based Recommendation
Ruining He, Wang-Cheng Kang, Julian McAuley
Modeling the complex interactions between users and items as well as amongst items themselves is at the core of designing successful recommender systems. One classical setting is p…
Sherlock: Sparse Hierarchical Embeddings for Visually-aware One-class Collaborative Filtering
Ruining He, Chunbin Lin, Jianguo Wang +1
Building successful recommender systems requires uncovering the underlying dimensions that describe the properties of items as well as users' preferences toward them. In domains li…
Fashionista: A Fashion-aware Graphical System for Exploring Visually Similar Items
Ruining He, Chunbin Lin, Julian McAuley
To build a fashion recommendation system, we need to help users retrieve fashionable items that are visually similar to a particular query, for reasons ranging from searching alter…