大数据与数字媒体传播中的个性化内容推荐技术  

Personalized content recommendation technology in big data and digital media communication

作　　者：丁一骁 杨树奎 康转怀 魏耀邦 DING Yixiao;YANG Shukui;KANG Zhuanhuai;WEI Yaobang(Gansu Science and Technology Museum,Lanzhou 730070,China)

机构地区：[1]甘肃科技馆,兰州730070

出　　处：《计算机应用文摘》2025年第8期78-80,共3页

摘　　要：大数据在数字媒体中的应用使得媒体机构能够从庞大的用户行为数据中提取有效信息,深度挖掘用户偏好、兴趣和消费习惯。通过智能算法,个性化推荐技术可以根据用户的历史行为、浏览记录、搜索关键词等数据精准匹配相关内容,从而为用户提供量身定制的资讯和娱乐服务。这种技术不仅提高了用户体验,减少了信息冗余,还有助于媒体机构提升内容传播效果,增加用户的停留时间和活跃度,从而增强用户粘性。此外,个性化内容推荐技术在新闻网站、视频平台、社交媒体等媒介平台的应用显著优化了信息分发效率,促使媒体行业从传统单向传播逐步向智能化、多元化的互动传播转型。The application of big data in digital media enables media organizations to extract effective information from a huge amount of user behavior data and deeply dig into user preferences,interests and consumption habits.Through intelligent algorithms,personalized recommendation technology can accurately match relevant content according to the user̓s historical behavior,browsing history,search keywords and other data,so as to provide users with tailored information and entertainment services.This technology not only improves the user experience and reduces information redundancy,but also helps media organizations improve the dissemination of content,increase user stay time and activity,and thus enhance user stickiness.In addition,the application of personalized content recommendation technology in news websites,video platforms,social media and other media platforms has significantly optimized the efficiency of information distribution,prompting the media industry to gradually transform from traditional one-way communication to intelligent and diversified interactive communication.

关 键 词：大数据 数字媒体 个性化推荐 用户行为分析 内容推荐算法 媒体传播创新 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]