计算机工程与科学2017，Vol.39Issue(6)：1179-1185,7.DOI:10.3969/j.issn.1007-130X.2017.06.023
一种基于改进型协同过滤算法的新闻推荐系统
A news recommendation system based on an improved collaborative filtering algorithm
摘要
Abstract
It is worth studying and exploring the research on the personalized recommendation technique that is used in news reader application to help users fast access interested news with its rapid and accurate features.We design and implement a news recommendation system based on user collaborative filtering recommendation technology.By collecting user data,calculating the reading time factor to correct user preference value,incorporating the influence of the news heat and punishing user similarity value by the heat,and then conducting Top-N ranking for user's unread news based on similar neighbor sets,the news of interest is pushed to the users.The test results of the news recommendation system show that it can provide real-time updates for the user interest model accurately and each function has achieved prospective design aim.关键词
个性化推荐/阅读耗时因子/Top-N排序Key words
personalized recommendation/reading time factor/Top-N ranking分类
信息技术与安全科学引用本文复制引用
吴彦文,齐旻,杨锐..一种基于改进型协同过滤算法的新闻推荐系统[J].计算机工程与科学,2017,39(6):1179-1185,7.基金项目
国家自然科学基金(71471073) （71471073）
湖北省高等学校省级教学研究项目(ccnu201439,ccnu201315) （ccnu201439,ccnu201315）
