摘要
微博作为一种重要的社交平台,聚集了大量用户生成的实时信息,如何从众多的微博中筛选出用户感兴趣的内容,成为亟待解决的问题。阐述了常用的推荐算法以及其存在的问题,提出了基于用户兴趣度的混合改进算法,探讨了混合推荐算法的改进效果。
As an important social platform,Weibo has accumulated a vast amount of real-time information generated by users.However,the challenge lies in how to filter out content of interest to users from the plethora of Weibo posts.This paper elucidates commonly used recommendation algorithms for Weibo and analyzes the issues prevalent in these approaches.We present a user-interest-based hybrid Weibo recommendation algorithm,exploring its enhancement effects.
作者
张兴宇
ZHANG Xingyu(Huainan Vocational and Technical College,Huainan Anhui 232001)
出处
《淮南职业技术学院学报》
2023年第4期146-149,共4页
Journal of Huainan Vocational Technical College
关键词
微博
用户兴趣度
协同推荐
混合算法
Weibo
user interest
collaborative filtering
hybrid algorithm
