Leveraging LLMs for optimised feature selection and embedding in structured data: A case study on graduate employment classification

Leveraging LLMs for optimised feature selection and embedding in structured data: A case study on graduate employment classification

The application of Machine Learning (ML) for predicting graduate student employability is a growing area of research, driven by the need to align educational outcomes with job market requirements. In this context, this paper investigates the application of Large Language Models (LLMs) for tabular da...

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Bibliographic Details
Main Authors: Radiah Haque, Hui-Ngo Goh, Choo-Yee Ting, Albert Quek, M.D. Rakibul Hasan
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Computers and Education: Artificial Intelligence
Subjects:
Machine learning
Student employability prediction
Feature selection
Large language models
BERT
Tabular data
Online Access:http://www.sciencedirect.com/science/article/pii/S2666920X24001590

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http://www.sciencedirect.com/science/article/pii/S2666920X24001590

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