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

A survey of recent techniques and architectures using large language models.

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

By Alma Smajić, Ratomir Karlović, Mieta Bobanović Dasko, Ivan LorencinElectronics
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This systematic review analyzes 88 studies on the use of large language models in recommendation systems, data processing, and knowledge base engineering. It highlights key trends and challenges, including hallucination mitigation, fairness, and domain adaptation.

The review also considers the broader macroeconomic implications of deploying LLM-based systems.

Abstract

This systematic review analyzes 88 studies on the use of large language models in recommendation systems, data processing, and knowledge base engineering. It highlights key trends and challenges, including hallucination mitigation, fairness, and domain adaptation. The review also considers the broader macroeconomic implications of deploying LLM-based systems.

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large language modelsrecommendation systemsknowledge base engineeringsystematic reviewai strategydata governanceLarge Language ModelsRetrieval & RAGStructured ContentContent Engineering
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