Natural Language Processing for Teaching and Research in Engineering Education

Topic

• Multi-source Machine Learning for Natural Language Relation Extraction in Education

Grant

• National Science Foundation (NSF) 2022
• Total: $299,647
• My share: $50,251

Objectives

• Enhancing engineering education decision making by combining pretrained text embedding transformers with nonlinear dimension reduction to extract hidden structures in data.

Team

• PI: Andrew Katz
• Co-PI: Hoda Eldardiry

Publications

• Clustering-based Unsupervised Generative Relation Extraction – IEEE Big Data 2023
• Knowledge-Enhanced Multi-Label Few-Shot Product Attribute-Value Extraction – ACM CIMK 2023