摘要
大数据技术和推荐算法可满足用户“定制化”需求与新闻信息多样化推荐,本文设计了基于集成学习的新闻推荐算法并在大数据系统中应用,最终形成了大象新闻APP的新闻推荐系统。该系统由河南广播电视台自主开发,在充分考虑用户需求和产业现状的前提下,实现了新闻的个性化、定制化推荐。
Big data technology and recommendation algorithm can meet the“customized”needs of users and the diversified recommendation of news information.This paper designs a news recommendation algorithm based on ensemble learning and applies it in the big data system,and finally forms the news recommendation system in the DAXIANG news app.The system is independently developed by Henan Radio and Television Station.On the premise of fully considering the needs of users and the current situation of the industry,it realizes the personalized and customized recommendation of news.
作者
张浩
Zhang Hao(Henan Radio and Television Station,Henan 450000,China)
出处
《广播与电视技术》
2022年第8期67-73,共7页
Radio & TV Broadcast Engineering
基金
“媒体融合与传播国家重点实验室(中国传媒大学)”开放课题资助(No.SKLMCC2021KF003)
河南省媒体融合平台与传播技术研究实验室支持。
关键词
算法
信息爆炸
新闻推荐
集成学习
Algorithm
Information explosion
News recommendation
Ensemble learning
