国防科技大学学报2025，Vol.47Issue(3)：10-20,11.DOI:10.11887/j.cn.202503002
多轮社交广告序列影响最大化
Multi-round social advertising sequence influence maximization
摘要
Abstract
Existing research on sequential ad recommendations mainly focuses on user preferences for advertisement,insufficiently considering positive relationships between ads.Starting from the associations between ads,incorporates both ad networks and user networks into consideration,a multi-round social advertising influence maximization model based on triggering model was constructed.An ad edge based greedy strategy based on multi-round reverse influence sampling was proposed to enhance platform revenue,with theoretical proofs of its strict lower bound guarantee.Experiments show that compared to existing optimal methods,the proposed method increases the average ad propagation influence revenue by 35％,significantly enhancing ad recommendation effectiveness,providing a new solution for ad sequence recommendations.关键词
社交网络/触发模型/影响力最大化/广告推荐Key words
social network/triggering model/influence maximization/advertising recommendation分类
计算机与自动化引用本文复制引用
付冰洋,张龙姣,史麒豪,王泽宇,王灿,宋明黎..多轮社交广告序列影响最大化[J].国防科技大学学报,2025,47(3):10-20,11.基金项目
国家自然科学基金资助项目(62372399) （62372399）
浙江大学上海高等研究院繁星科学基金资助项目(SN-ZJU-SIAS-001) （SN-ZJU-SIAS-001）
