1.5k citations · 6.3k across the 35 of their papers we have counts for
7 papers · 1 filter
Fake News Detection through Graph Comment Advanced Learning
Hao Liao, Qixin Liu, Kai Shu +1
Disinformation has long been regarded as a severe social problem, where fake news is one of the most representative issues. What is worse, today's highly developed social media mak…
PTUM: Pre-training User Model from Unlabeled User Behaviors via Self-supervision
Chuhan Wu, Fangzhao Wu, Tao Qi +3
User modeling is critical for many personalized web services. Many existing methods model users based on their behaviors and the labeled data of target tasks. However, these method…
FedCTR: Federated Native Ad CTR Prediction with Multi-Platform User Behavior Data
Chuhan Wu, Fangzhao Wu, Tao Di +2
Native ad is a popular type of online advertisement which has similar forms with the native content displayed on websites. Native ad CTR prediction is useful for improving user exp…
FairRec: Fairness-aware News Recommendation with Decomposed Adversarial Learning
Chuhan Wu, Fangzhao Wu, Xiting Wang +2
News recommendation is important for online news services. Existing news recommendation models are usually learned from users' news click behaviors. Usually the behaviors of users…
FedNER: Privacy-preserving Medical Named Entity Recognition with Federated Learning
Suyu Ge, Fangzhao Wu, Chuhan Wu +3
Medical named entity recognition (NER) has wide applications in intelligent healthcare. Sufficient labeled data is critical for training accurate medical NER model. However, the la…
Privacy-Preserving News Recommendation Model Learning
Tao Qi, Fangzhao Wu, Chuhan Wu +2
News recommendation aims to display news articles to users based on their personal interest. Existing news recommendation methods rely on centralized storage of user behavior data…
A Survey on Knowledge Graph-Based Recommender Systems
Qingyu Guo, Fuzhen Zhuang, Chuan Qin +4
To solve the information explosion problem and enhance user experience in various online applications, recommender systems have been developed to model users preferences. Although…