A survey of personalized news recommendation
X Meng, H Huo, X Zhang, W Wang, J Zhu - Data Science and Engineering, 2023 - Springer
Personalized news recommendation is an important technology to help users obtain news
information they are interested in and alleviate information overload. In recent years, news …
information they are interested in and alleviate information overload. In recent years, news …
Personalized news recommendation: Methods and challenges
Personalized news recommendation is important for users to find interesting news
information and alleviate information overload. Although it has been extensively studied …
information and alleviate information overload. Although it has been extensively studied …
Feedrec: News feed recommendation with various user feedbacks
Accurate user interest modeling is important for news recommendation. Most existing
methods for news recommendation rely on implicit feedbacks like click for inferring user …
methods for news recommendation rely on implicit feedbacks like click for inferring user …
Dual personalization on federated recommendation
Federated recommendation is a new Internet service architecture that aims to provide
privacy-preserving recommendation services in federated settings. Existing solutions are …
privacy-preserving recommendation services in federated settings. Existing solutions are …
A generic federated recommendation framework via fake marks and secret sharing
With the implementation of privacy protection laws such as GDPR, it is increasingly difficult
for organizations to legally collect users' data. However, a typical machine learning-based …
for organizations to legally collect users' data. However, a typical machine learning-based …
Fedprompt: Communication-efficient and privacy-preserving prompt tuning in federated learning
Federated learning (FL) has enabled global model training on decentralized data in a
privacy-preserving way. However, for tasks that utilize pre-trained language models (PLMs) …
privacy-preserving way. However, for tasks that utilize pre-trained language models (PLMs) …
Towards Federated Large Language Models: Motivations, Methods, and Future Directions
Y Cheng, W Zhang, Z Zhang, C Zhang… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Large Language Models (LLMs), such as LLaMA and GPT-4, have transformed the
paradigm of natural language comprehension and generation. Despite their impressive …
paradigm of natural language comprehension and generation. Despite their impressive …
ProFairRec: Provider fairness-aware news recommendation
News recommendation aims to help online news platform users find their preferred news
articles. Existing news recommendation methods usually learn models from historical user …
articles. Existing news recommendation methods usually learn models from historical user …
News recommendation with candidate-aware user modeling
News recommendation aims to match news with personalized user interest. Existing
methods for news recommendation usually model user interest from historical clicked news …
methods for news recommendation usually model user interest from historical clicked news …
A survey on federated recommendation systems
Federated learning has recently been applied to recommendation systems to protect user
privacy. In federated learning settings, recommendation systems can train recommendation …
privacy. In federated learning settings, recommendation systems can train recommendation …