Scientific Event Recommendation through Semantic Clustering and Embedding Analysis - Silva, Karla S.; Rezende, Rebeca L.; Silva, João V. D.; Cardoso, Gabriel; Ventura, Thiago M.; Oliveira, Allan G. de (Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC), 2025)
This work presents a series of experiments aimed at recommending scientific events within the Brazilian Computer Society (SBC), leveraging semantic embeddings generated by Large Language Models (LLMs) and unsupervised clustering techniques. Using BERTopic for topic modeling and multilingual representations, the experimental approach processes over 12,000 articles from 30 events to align submissions with relevant themes. The best configuration reached an accuracy of 0.91 and demonstrates the potential of LLM-based embeddings to support decision-making in scientific dissemination.