An Comparative Analysis about KYC on a Recommendation System Toward Agentic Recommendation System
On the map: LLM agents and tool use → Agentic recommender systems
Abstract (arXiv)
This research presents a cutting-edge recommendation system utilizing agentic AI for KYC (Know Your Customer in the financial domain), and its evaluation across five distinct content verticals: Advertising (Ad), News, Gossip, Sharing (User-Generated Content), and Technology (Tech). The study compares the performance of four experimental groups, grouping by the intense usage of KYC, benchmarking them against the Normalized Discounted Cumulative Gain (nDCG) metric at truncation levels of k=1, k=3, and k=5. By synthesizing experimental data with theoretical frameworks and industry benchmarks from platforms such as Baidu and Xiaohongshu, this research provides insight by showing experimental results for engineering a large-scale agentic recommendation system.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Agentic recommender systems, one of 16 directions in LLM agents and tool use. Builds on 2 of its 11 references that are in the map. First posted on arXiv 30 Dec 2025.
Builds on
2 of 11 references.
References · 2
- 2025AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challengescited by 169
- 2013A Theoretical Analysis of NDCG Type Ranking Measurescited by 119
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