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MAS4POI: a Multi-Agents Collaboration System for Next POI Recommendation

About

LLM-based Multi-Agent Systems have potential benefits of complex decision-making tasks management across various domains but their applications in the next Point-of-Interest (POI) recommendation remain underexplored. This paper proposes a novel MAS4POI system designed to enhance next POI recommendations through multi-agent interactions. MAS4POI supports Large Language Models (LLMs) specializing in distinct agents such as DataAgent, Manager, Analyst, and Navigator with each contributes to a collaborative process of generating the next POI recommendations.The system is examined by integrating six distinct LLMs and evaluated by two real-world datasets for recommendation accuracy improvement in real-world scenarios. Our code is available at https://github.com/yuqian2003/MAS4POI.

Yuqian Wu, Yuhong Peng, Jiapeng Yu, Raymond S. T. Lee• 2024

Related benchmarks

TaskDatasetResultRank
POI RecommendationFoursquare-NYC Standard Evaluation (test)
Recall@518.3
10
POI RecommendationFoursquare-TKY Standard Evaluation (test)
Recall@516.7
10
POI RecommendationYelp-Open Standard Evaluation (test)
R@510.6
10
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