语境是不是很重要? 精心调整的上下文增强在社交媒体上在线广告交付中的作用
Saifullah Jan1, Iftikhar Alam1, Inayat Khan2
1Department of Computer Science, City University of Science and Information Technology, Peshawar, Pakistan.
Big data
|December 30, 2025
概括
本研究引入了一个实时的,适应环境的广告推框架. 它通过动态更新用户上下文来提高广告相关性和用户参与度,从而提高了转化率.
科学领域:
- 人工智能的人工智能
- 计算机科学 计算机科学
- 电子商务 技术 技术 电子商务
背景情况:
- 目前的数字广告实践往往使用非上下文广告,导致用户参与度较低,广告跳过率高,商业化效率低.
- 不相关的广告会导致低转化率和用户丧,这凸显了对更个性化和上下文意识的广告解决方案的需求.
研究的目的:
- 开发一个实时的,适应上下文的广告推框架,动态更新用户上下文,以提供个性化的广告.
- 通过通过语义丰富和上下文感知系统将广告与用户兴趣相协调,提高广告相关性,用户参与度和转化率.
主要方法:
- 拟议的框架集成了用户上下文提取器 (UCE),推系统,广告数据库,广告排名器和广告过器.
- 一个多阶段的排名和过管道被用于实时提供高度相关和个性化的广告.
- 该系统使用基于k-最近邻居的模型进行评估,以评估其性能.
主要成果:
- 环境适应框架显示了精度 (0.8275到0.9283),回忆 (0.4628到0.5201) 和正常化的折扣累积收益 (0.9906到0.9915) 的显著改进.
- 整合细粒度,动态的用户环境大大提高了推质量和用户参与度.
- 该系统为智能,自适应式广告系统提供了一个可扩展的基础.
结论:
- 开发的框架通过利用动态用户环境,有效提高广告相关性和用户参与度,从而提高点击率和客户满意度.
- 这种方法减少了广告疲劳和广告回避,因为用户可以根据他们的兴趣提供相关的内容.
- 该研究有助于开发基于人工智能的广告策略,专注于动态广告定位,个性化和改善业务转化率.
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