Semantic Prompting over Knowledge Graphs for Next-Generation Recommender Systems

Antony Seabra, Claudio Cavalcante, Sergio Lifschitz

2025

Abstract

This paper presents a novel recommender system framework that integrates Knowledge Graphs (KGs) and Large Language Models (LLMs) through dynamic semantic prompt generation. Rather than relying on static templates or embeddings alone, the system dynamically constructs natural language prompts by traversing RDF-based knowledge graphs and extracting relevant entity relationships tailored to the user and recommendation task. These semantically enriched prompts serve as the interface between structured knowledge and the generative capabilities of LLMs, enabling more coherent and context-aware suggestions. We validate our approach in three practical scenarios: personalized product recommendation, identification of users for targeted marketing, and product bundling optimization. Results demonstrate that aligning prompt construction with domain semantics significantly improves recommendation quality and consistency. The paper also discusses strategies for prompt generation, template abstraction, and knowledge selection, highlighting their impact on the robustness and adaptability of the system.

Paper Citation

in Harvard Style

Seabra A., Cavalcante C. and Lifschitz S. (2025). Semantic Prompting over Knowledge Graphs for Next-Generation Recommender Systems. In Proceedings of the 21st International Conference on Web Information Systems and Technologies - Volume 1: WEBIST; ISBN 978-989-758-772-6, SciTePress, pages 394-403. DOI: 10.5220/0013741700003985

in Bibtex Style

@conference{webist25,
author={Antony Seabra and Claudio Cavalcante and Sergio Lifschitz},
title={Semantic Prompting over Knowledge Graphs for Next-Generation Recommender Systems},
booktitle={Proceedings of the 21st International Conference on Web Information Systems and Technologies - Volume 1: WEBIST},
year={2025},
pages={394-403},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013741700003985},
isbn={978-989-758-772-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 21st International Conference on Web Information Systems and Technologies - Volume 1: WEBIST
TI - Semantic Prompting over Knowledge Graphs for Next-Generation Recommender Systems
SN - 978-989-758-772-6
AU - Seabra A.
AU - Cavalcante C.
AU - Lifschitz S.
PY - 2025
SP - 394
EP - 403
DO - 10.5220/0013741700003985
PB - SciTePress