Paper Info
Title
Factual Question Generation for the Portuguese Language
Abstract
Artificial Intelligence (AI) has seen numerous applications in the area of Education. Through the use of educational technologies such as Intelligent Tutoring Systems (ITS), learning possibilities have increased significantly. One of the main challenges for the widespread use of ITS is the ability to automatically generate questions. Bearing in mind that the act of questioning has been shown to improve the students learning outcomes, Automatic Question Generation (AQG) has proven to be one of the most important applications for optimizing this process. We present a tool for generating factual questions in Portuguese by proposing three distinct approaches. The first one performs a syntax-based analysis of a given text by using the information obtained from Part-of-speech tagging (PoS) and Named Entity Recognition (NER). The second approach carries out a semantic analysis of the sentences, through Semantic Role Labeling (SRL). The last method extracts the inherent dependencies within sentences using Dependency Parsing. All of these methods are possible thanks to Natural Language Processing (NLP) techniques. For evaluation, we have elaborated a pilot test that was answered by Portuguese teachers. The results verify the potential of these different approaches, opening up the possibility to use them in a teaching environment.
Year
DOI
Venue
2020
10.1109/INISTA49547.2020.9194631
2020 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)
Keywords
DocType
ISBN
Natural Language Processing,Automatic Question Generation,Named Entity Recognition,Semantic Role Labeling,Dependency Parsing
Conference
978-1-7281-6800-5
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Bernardo Leite100.34
Henrique Lopes Cardoso222334.02
Luís Paulo Reis348283.34
Carlos Guedes Soares48421.43