Zhiping Xiao

DisCo: Graph-Based Disentangled Contrastive Learning for Cold-Start Cross-Domain Recommendation

2024 · arXiv (Cornell University)

Recommender systems are widely used in various real-world applications, but they often encounter the persistent challenge of the user cold-start problem. Cross-domain recommendation (CDR), which leverages user interactions from one domain to improve prediction performance …

AutoInt

2019

Click-through rate (CTR) prediction, which aims to predict the probability of a user clicking on an ad or an item, is critical to many online applications such as online advertising and recommender systems. The problem …

Session-Based Social Recommendation via Dynamic Graph Attention Networks

2019

Online communities such as Facebook and Twitter are enormously popular and have become an essential part of the daily life of many of their users. Through these platforms, users can discover and create information that …