UFGraphFR: Graph Federation Recommendation System based on User Text description features

UFGraphFR is a novel recommendation system designed to enhance user privacy by leveraging federated learning techniques. It addresses the challenge of data localization by constructing global user relationship graphs without centralizing sensitive information. This approach improves the accuracy of recommendations by enabling better collaboration and insights derived from distributed user data. The system utilizes user text description features to build these graphs, facilitating more personalized and relevant suggestions. By maintaining data privacy and overcoming localization constraints, UFGraphFR represents an advancement in recommendation technology. Its federated learning foundation ensures that user data remains decentralized while still contributing to a global model. This balance between privacy and performance marks a significant improvement in recommendation systems.