基于流程挖掘和深度学习的融媒节目生产预测技术研究与实践  

Research and Practice on the Prediction Technology of Integrated Media Programme Production Based on Process Mining and Deep Learning

作　　者：郑观卫 禚春升 徐兴荣 Zheng Guanwei;Zhuo Chunsheng;Xu Xingrong(Zibo Radio and Television Station,Shandong 255000,China)

机构地区：[1]淄博市广播电视台,山东255000

出　　处：《广播与电视技术》2025年第1期46-50,共5页Radio & TV Broadcast Engineering

摘　　要：本文基于融媒体节目生产并结合流程挖掘技术和深度学习算法,针对市级广播电视台融媒体平台建设,提出了一种素材编辑剩余时间预测方法与多任务协调机制,可以实现智能化素材编辑剩余时间预测和素材推荐,能有效提升内容制播效果和工作效率。Based on the production of integrated media programs and combining process mining technology and deep learning algorithms,this paper proposes a method for predicting remaining time in material editing and a multi-task coordination mechanism for constructing integrated media platforms for municipal radio and television stations.It can achieve intelligent prediction of the remaining time in material editing and material recommendation,effectively improving content production and broadcasting effects and work efficiency.

关 键 词：深度学习 流程挖掘 融媒体节目生产 剩余时间预测 多任务协调 

分 类 号：TP302.1[自动化与计算机技术—计算机系统结构]