西华大学学报（自然科学版）2025，Vol.44Issue(2)：79-86,8.DOI:10.12198/j.issn.1673-159X.4864
基于RippleNet的实体加权新闻推荐
Entity Weighted News Recommendation Based on RippleNet
摘要
Abstract
Recommendation system has always been a hot issue in information retrieval research.Compared with other items such as movie recommendation and travel recommendation,news recommenda-tion has the characteristics of large batch of news articles and strong timeliness,which has higher require-ments on the algorithm.Based on the RippleNet model,this paper introduces the concept of entity entry de-gree,which highlights the importance of individual entities by weighting multilateral entities,thus improv-ing the accuracy of news recommendation.The performance validation on the news dataset shows that the overall accuracy of this model is improved by 1.7%compared with other baseline models.关键词
推荐系统/新闻推荐/RippleNet/实体入度Key words
recommendation system/news recommendation/RippleNet/entity in-degree分类
计算机与自动化引用本文复制引用
黄华靖,韩梅,刘康民,刘翥,范永全..基于RippleNet的实体加权新闻推荐[J].西华大学学报（自然科学版）,2025,44(2):79-86,8.基金项目
国家自然科学基金项目(61872298、61802316、61902324) （61872298、61802316、61902324）
四川省科技创新苗子工程(2015075) （2015075）
四川省科技厅项目(2023YFQ0044) （2023YFQ0044）
西华大学研究生科创竞赛项目(YK20240148). （YK20240148）
