News Recommendation
66 papers with code • 1 benchmarks • 6 datasets
Most implemented papers
Contextual Hybrid Session-based News Recommendation with Recurrent Neural Networks
The recommendation of news is often considered to be challenging, since the relevance of an article for a user can depend on a variety of factors, including the user's short-term reading interests, the reader's context, or the recency or popularity of an article.
Privacy-Preserving News Recommendation Model Learning
Extensive experiments on a real-world dataset show the effectiveness of our method in news recommendation model training with privacy protection.
MIND: A Large-scale Dataset for News Recommendation
News recommendation is an important technique for personalized news service.
ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models
Personalized content-based recommender systems have become indispensable tools for users to navigate through the vast amount of content available on platforms like daily news websites and book recommendation services.
Train Once, Use Flexibly: A Modular Framework for Multi-Aspect Neural News Recommendation
Recent neural news recommenders (NNR) extend content-based recommendation by (1) aligning additional aspects such as topic or sentiment between the candidate news and user history or (2) diversifying recommendations w. r. t.
A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems
We extend the model to jointly learn from features of items from different domains and user features by introducing a multi-view Deep Learning model.
Representation learning for very short texts using weighted word embedding aggregation
Traditional textual representations, such as tf-idf, have difficulty grasping the semantic meaning of such texts, which is important in applications such as event detection, opinion mining, news recommendation, etc.
The Graph-Based Behavior-Aware Recommendation for Interactive News
First, we build an interaction behavior graph for multi-level and multi-category data.
Content based News Recommendation via Shortest Entity Distance over Knowledge Graphs
Content-based news recommendation systems need to recommend news articles based on the topics and content of articles without using user specific information.
Neural News Recommendation with Long- and Short-term User Representations
In this paper, we propose a neural news recommendation approach which can learn both long- and short-term user representations.