AI RESEARCH
A Hybrid Machine Learning Approach for Graduate Admission Prediction and Combined University-Program Recommendation
arXiv CS.LG
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ArXi:2603.29881v1 Announce Type: cross Graduate admissions have become increasingly competitive. This study highlights the need for a hybrid machine learning framework for graduate admission prediction, focusing on high-quality similar applicants and a recommendation system. The dataset, collected and enriched by the authors, includes 13,000 self-reported GradCafe application records from 2021 to 2025, enriched with features from the OpenAlex API, QS World University Rankings by Subject, and Wikidata SPARQL queries.