Development of natural language processing techniques for information extraction from scientific articles

• Grant number: 25/03245-1
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: May 01, 2025
• End date: April 30, 2028
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Elbert Einstein Nehrer Macau
• Grantee: Ricardo Trainotti Rabonato
• Host Institution: Instituto de Ciência e Tecnologia (ICT). Universidade Federal de São Paulo (UNIFESP). Campus São José dos Campos. São José dos Campos , SP, Brazil
• Associated research grant: 21/10599-3 - The Antimicrobial Resistance Institute of São Paulo (The Aries Project), AP.CEPID

Abstract

Scientific articles contain a wealth of valuable information, but extracting and organizing this information manuallycan be time-consuming and labor-intensive. Natural Language Processing (NLP) techniques offer a promisingsolution to automate the extraction of relevant information from scientific articles. This project aims to developadvanced NLP techniques to enhance information extraction from scientific literature. In this project, we willdevelop NLP techniques to select the most relevant information by leveraging state-of-the-art models andalgorithms. Through the application of NLP methods, we seek to extract key insights, relationships, and findingsfrom vast amounts of scientific texts, thereby facilitating knowledge discovery and synthesis in various domains.