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008
Publications

2021

Novelty Detection in Physical Activity

Authors
Leite, B; Abdalrahman, A; Castro, J; Frade, J; Moreira, J; Soares, C;

Publication
Proceedings of the 13th International Conference on Agents and Artificial Intelligence, ICAART 2021, Volume 2, Online Streaming, February 4-6, 2021.

Abstract

2021

Micro-MetaStream: Algorithm selection for time-changing data

Authors
Rossi, ALD; Soares, C; de Souza, BF; de Carvalho, ACPDF;

Publication
INFORMATION SCIENCES

Abstract
Data stream mining needs to deal with scenarios where data distribution can change over time. As a result, different learning algorithms can be more suitable in different time periods. This paper proposes micro-MetaStream, a meta-learning based method to recommend the most suitable learning algorithm for each new example arriving in a data stream. It is an evolution of MetaStream, which recommends learning algorithms for batches of examples. By using a unitary granularity, micro-MetaStream is able to respond more efficiently to changes in data distribution than its predecessor. The meta-data combines meta-features, characteristics describing recent data, with base-level features, the original variables of the new example. In experiments on real-world regression data streams, micro-metaStream outperformed MetaStream and a baseline method at the meta-level and frequently improved the predictive performance at the base-level.

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.

Supervised
thesis

2019

Dataset morphing to analyze the performance of recommender systems

Author
André Gomes Ferreira Araújo Correia

Institution
UP-FEUP

2019

Automatic Interpretation of Promotional Leaflets in Retail for Pricing Strategy

Author
António Maria Aires Pereira Teixeira de Melo

Institution
UP-FEUP

2019

Automated Feature Engineering for Classification Problems

Author
Guilherme Felipe do Nascimento Reis

Institution
UP-FEUP

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