How can I target ads in transit systems using AI agents?
Context-aware Advertisement Modeling and Applications in Rapid Transit Systems
September 17, 2024
https://arxiv.org/pdf/2409.09956This paper proposes a multi-agent system for optimizing advertisement placement within rapid transit systems. It leverages user travel patterns, social media activity, and contextual information like nearby buildings to display relevant ads.
Key points for LLM-based multi-agent systems:
- Agent-based modeling (ABM) is used to simulate the interactions between users, brands, transit stations, and advertisement screens.
- Data mining techniques like DBSCAN are applied to GPS data and social media activity to identify patterns and cluster users.
- Contextual information like time of day and nearby businesses influences ad selection.
- The system demonstrates how LLMs can personalize user experiences by leveraging diverse data sources and dynamically adapting to real-time feedback.