August 7, 2025ElectronicsOpen Access

Large Language Models for Structured and Semi-Structured Data, Recommender Systems and Knowledge Base Engineering: A Survey of Recent Techniques and Architectures

View Full Paper

Ask AI

Bookmark

Authors

Discussion

This systematic review analyzes 88 studies on large language models in recommendation systems, highlighting key trends and challenges.

LLMs enhance recommendation systems by improving semantic reasoning and personalization, addressing user needs more effectively.
The review identifies key technical advancements, including knowledge graphs and Retrieval-Augmented Generation, impacting system performance.
Employing systematic methods, it categorizes findings into data processing and LLM-based architectures for better comprehension.
The analysis suggests ongoing challenges in fairness and hallucination mitigation, underscoring a need for robust solutions in deployment.

Smajić et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark