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Textual inference applied to Question and Answering Systems

Grant number: 13/22973-0
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): May 01, 2014
Effective date (End): February 28, 2018
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal Investigator:Sandra Maria Aluísio
Grantee:Erick Rocha Fonseca
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Associated scholarship(s):16/02466-5 - Deep neural networks for semantic alignments and recognizing textual entailment, BE.EP.DR

Abstract

This project aims the development of methods for the field of Question Answering (QA) and the implementation of a system that will employ them. Natural Language Processing techniques are intended to be explored in order to perform transformations in small portions of text, which should make them easier for processing, while keeping their original meaning. Thus, a QA system can have more flexibility when dealing with questions and text bases that talk about the same subjects, but written differently. In particular, the system is intended to be directed to the domain of chemical and contamination risk in the milk production chain, because this project is carried out in partnership with a research network about the domain and which involves other institutions.

Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
FONSECA, Erick Rocha. Recognizing textual entailment in Portuguese. 2018. Doctoral Thesis - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação São Carlos.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.