Research on AI-Driven Advertising Optimization and Automated Decision System

Qingyang Zhang

European Journal of Business, Economics & Management, 2025, vol. 1, issue 2, 62-68

Abstract: This paper conducts an in-depth exploration of the introduction of artificial intelligence technology in the advertising placement process. Centered on the user behavior pattern constructed with deep learning as the core and the process-based advertising decision-making applying reinforcement learning, an artificial intelligence-driven advertising placement system is constructed, including functions such as data collection and processing, model training and optimization, automated decision-making, and automatic placement control. After practical verification, it can significantly enhance the intelligence of advertising placement and the efficiency of resource allocation, and has promising application prospects and significant social value.

Keywords: artificial intelligence; advertising placement; deep learning; reinforcement learning; automated decision-making (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://pinnaclepubs.com/index.php/EJBEM/article/view/156/158 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:dba:ejbema:v:1:y:2025:i:2:p:62-68

Access Statistics for this article

More articles in European Journal of Business, Economics & Management from Pinnacle Academic Press
Bibliographic data for series maintained by Joseph Clark ().