Weizhi Ma

Standing in Your Shoes: External Assessments for Personalized Recommender Systems

2021

The evaluation of recommender systems relies on user preference data, which is difficult to acquire directly because of its subjective nature. Current recommender systems widely utilize users' historical interactions as implicit or explicit feedback, but …

Aligning Explanations for Recommendation with Rating and Feature via Maximizing Mutual Information

2024 · arXiv (Cornell University)

Providing natural language-based explanations to justify recommendations helps to improve users' satisfaction and gain users' trust. However, as current explanation generation methods are commonly trained with an objective to mimic existing user reviews, the generated …

Understanding Internal Representations of Recommendation Models with Sparse Autoencoders

2026 · ACM Transactions on Information Systems

Recommendation model interpretation aims to reveal the relationships between inputs, model internal representations, and outputs to enhance the transparency, interpretability, and trustworthiness of recommendation systems. However, the inherent complexity and opacity of deep learning models …

Jointly Learning Explainable Rules for Recommendation with Knowledge Graph

2019

Explainability and effectiveness are two key aspects for building recommender systems. Prior efforts mostly focus on incorporating side information to achieve better recommendation performance. However, these methods have some weaknesses: (1) prediction of neural network-based …

An Efficient Adaptive Transfer Neural Network for Social-aware Recommendation

2019

Many previous studies attempt to utilize information from other domains to achieve better performance of recommendation. Recently, social information has been shown effective in improving recommendation results with transfer learning frameworks, and the transfer part …

A Survey on the Fairness of Recommender Systems

2022 · ACM Transactions on Information Systems

Recommender systems are an essential tool to relieve the information overload challenge and play an important role in people’s daily lives. Since recommendations involve allocations of social resources (e.g., job recommendation), an important issue is …