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007
Publications

2020

Building Robust Prediction Models for Defective Sensor Data Using Artificial Neural Networks

Authors
de Sa, CR; Shekar, AK; Ferreira, H; Soares, C;

Publication
Advances in Intelligent Systems and Computing - 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019)

Abstract

2020

Process discovery on geolocation data

Authors
Ribeiro, J; Fontes, T; Soares, C; Borges, JL;

Publication
Transportation Research Procedia

Abstract

2020

Factual Question Generation for the Portuguese Language

Authors
Leite, B; Cardoso, HL; Reis, LP; Soares, C;

Publication
International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2020, Novi Sad, Serbia, August 24-26, 2020

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. © 2020 IEEE.

2020

Fraunhofer AICOS at CLEF eHealth 2020 Task 1: Clinical Code Extraction From Textual Data Using Fine-Tuned BERT Models

Authors
Costa, J; Lopes, I; Carreiro, A; Ribeiro, D; Soares, C;

Publication
Working Notes of CLEF 2020 - Conference and Labs of the Evaluation Forum, Thessaloniki, Greece, September 22-25, 2020.

Abstract

2020

Underground Train Tracking using Mobile Phone Accelerometer Data

Authors
Baghoussi, Y; Moreira, JM; Moniz, N; Soares, C;

Publication
23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020, Rhodes, Greece, September 20-23, 2020

Abstract

Supervised
thesis

2019

Learning to Rank with Random Forest: A Case Study in Hostel Reservations

Author
Carolina Macedo Moreira

Institution
UP-FEUP

2019

sistema de apoio à escolha de algoritmos para problemas de optimização

Author
Pedro Manuel Correia de Abreu

Institution
UP-FEUP

2019

Prescriptive Analytics for Staff Scheduling Optimization in Retail

Author
Catarina Alexandra Teixeira Ramos

Institution
UP-FEUP

2019

Recommending Recommender Systems: tackling the Collaborative Filtering algorithm selection problem

Author
Tiago Daniel Sá Cunha

Institution
UP-FEUP

2019

An optimization-based wrapper approach for utility-based data mining

Author
José Francisco Cagigal da Silva Gomes

Institution
UP-FEUP