Jing Yao

Learning to Select Historical News Articles for Interaction based Neural News Recommendation

2021 · arXiv (Cornell University)

The key to personalized news recommendation is to match the user's interests with the candidate news precisely and efficiently. Most existing approaches embed user interests into a representation vector then recommend by comparing it with …

Towards Explainable Collaborative Filtering with Taste Clusters Learning

2023

Collaborative Filtering (CF) is a widely used and effective technique for recommender systems. In recent decades, there have been significant advancements in latent embedding-based CF methods for improved accuracy, such as matrix factorization, neural collaborative …

Neural Recommendation Reasoning with Logic Rules

2025 · ACM Transactions on Information Systems

Explainability is critical for recommender systems to ensure good user experience and facilitate designers to debug. However, generating explanations in recommender systems usually requires large efforts due to the dependency on additional data and case-by-case …