Influenced by the great success of deep learning in computer vision and language
understanding, research in recommendation has shifted to inventing new recommender …

Digital journalism has faced a dramatic change and media companies are challenged to use
data science algorithms to be more competitive in a Big Data era. While this is a relatively …

Federated learning is a privacy-preserving machine learning technique to train intelligent
models from decentralized data, which enables exploiting private data by communicating …

News recommendation is an important technique for personalized news service. Compared
with product and movie recommendations which have been comprehensively studied, the …

News recommendation can help users find interested news and alleviate information
overload. Precisely modeling news and users is critical for news recommendation, and …

News recommendation is very important to help users find interested news and alleviate
information overload. Different users usually have different interests and the same user may …

Some recent news recommendation (NR) methods introduce a Pre-trained Language Model
(PLM) to encode news representation by following the vanilla pre-train and fine-tune …

Personalized news recommendation is an essential technique for online news services.
News articles usually contain rich textual content, and accurate news modeling is important …

In order to support the study of recent advances in recommender systems, this paper
presents an extended recommendation library consisting of eight packages for up-to-date …

Nowadays, news recommendation has become a popular channel for users to access news
of their interests. How to represent rich textual contents of news and precisely match users' …