Keywords
Structured Review
Artificial Intelligence
Natural Language Processing
How to Cite
Abstract
This article presents a structured literature review on recommender systems that use natural language processing (NLP), covering publications between 2020 and 2025. The final corpus included 240 fully analyzed articles after screening and deduplication (214 from 2020-2024 and 26 from 2025). Digital tools such as Zotero, Rayyan, SciSpace, NotebookLM, and Biblioshiny supported data curation and organization. The results highlight the predominance of deep learning techniques, with emphasis on models such as BERT, Word2Vec, and GPT, as well as the growing use of large language models (LLMs) and knowledge graphs. However, no records were found in the Revista Brasileira de Informática na Educação (RBIE) or the digital library of the Sociedade Brasileira de Computação (SBC-OpenLib), showing that, compared to global domains, scientific production in specific national niches is still incipient. This gap highlights relevant opportunities for transposing advanced natural language processing techniques to specific domains that are still underexplored at a national level, such as the educational context, in addition to fostering the training of researchers in the use of artificial intelligence-assisted systematic review methodologies.
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