Jean Paul Barddal

Simon Bernard

Stat. Comput., February, 2024

Temporal analysis of drifting hashtags in textual data streams: A graph-based application.

[BibT_eX]

[DOI]

Cinthia Obladen de Almendra Freitas

Expert Syst. Appl., 2024

LongKey: Keyphrase Extraction for Long Documents.

[BibT_eX]

[DOI]

Jeovane Honório Alves

Radu State

Luiz Carlos Ribeiro Neduziak

CoRR, 2024

Dynamic Modality and View Selection for Multimodal Emotion Recognition with Missing Modalities.

[BibT_eX]

[DOI]

Luciana Trinkaus Menon

Alceu de Souza Britto Jr

CoRR, 2024

Methods for Generating Drift in Text Streams.

[BibT_eX]

[DOI]

CoRR, 2024

Adaptive learning on hierarchical data streams using window-weighted Gaussian probabilities.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2024

Just Change on Change: Adaptive Splitting Time for Decision Trees in Data Stream Classification.

[BibT_eX]

[DOI]

Daniel Nowak Assis

Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, 2024

Alleviating Catastrophic Forgetting in Facial Expression Recognition with Emotion-Centered Models.

[BibT_eX]

[DOI]

Israel A. Laurensi R.

Proceedings of the Pattern Recognition - 27th International Conference, 2024

Improving Sampling Methods for Fine-Tuning SentenceBERT in Text Streams.

[BibT_eX]

[DOI]

Alceu de Souza Britto Junior

João Gabriel Corrêa Krüger

Proceedings of the Pattern Recognition - 27th International Conference, 2024

2023

An explainable machine learning approach for student dropout prediction.

[BibT_eX]

[DOI]

Expert Syst. Appl., December, 2023

Incremental specialized and specialized-generalized matrix factorization models based on adaptive learning rate optimizers.

[BibT_eX]

[DOI]

Antônio David Viniski

Alceu de Souza Britto Junior

Humberto Vinicius Aparecido de Campos

Neurocomputing, October, 2023

Exploring diversity in data complexity and classifier decision spaces for pool generation.

[BibT_eX]

[DOI]

Marcos Monteiro

Alceu de Souza Britto Junior

Luiz S. Oliveira

Robert Sabourin

Inf. Fusion, 2023

Concept Drift Adaptation in Text Stream Mining Settings: A Comprehensive Review.

[BibT_eX]

[DOI]

Ramon Simoes Abilio

CoRR, 2023

Random Forest Dissimilarity for High-Dimension Low Sample Size Classification.

[BibT_eX]

[DOI]

Simon Bernard

CoRR, 2023

Benchmarking Feature Extraction Techniques for Textual Data Stream Classification.

[BibT_eX]

[DOI]

Bruno Siedekum Thuma

Pedro Silva de Vargas

Proceedings of the International Joint Conference on Neural Networks, 2023

Mass-Based Short Term Selection of Classifiers in Data Streams.

[BibT_eX]

[DOI]

Daniel Nowak Assis

Proceedings of the International Joint Conference on Neural Networks, 2023

Deep Single Models vs. Ensembles: Insights for a Fast Deployment of Parking Monitoring Systems.

[BibT_eX]

[DOI]

Andre Gustavo Hochuli

Paulo Ricardo Lisboa de Almeida

Gillian Cezar Palhano

Leonardo Matheus Mendes

Proceedings of the International Conference on Machine Learning and Applications, 2023

Event-driven Sentiment Drift Analysis in Text Streams: An Application in a Soccer Match.

[BibT_eX]

[DOI]

Rafael Honorio Venetikides

Proceedings of the International Conference on Machine Learning and Applications, 2023

Detecting Relevant Information in High- Volume Chat Logs: Keyphrase Extraction for Grooming and Drug Dealing Forensic Analysis.

[BibT_eX]

[DOI]

Jeovane Honório Alves

Horácio A. C. G. Pedroso

Joel E. M. Köster

Luiz Rodrigo Grochocki

Cinthia O. A. Freitas

Eric Kenzo Taniguchi Onuki

Proceedings of the International Conference on Machine Learning and Applications, 2023

A Tool for Measuring Energy Consumption in Data Stream Mining.

[BibT_eX]

[DOI]

Paulo Ricardo Lisboa de Almeida

Proceedings of the Intelligent Systems - 12th Brazilian Conference, 2023

2022

A systematic review on computer vision-based parking lot management applied on public datasets.

[BibT_eX]

[DOI]

Jeovane Honório Alves

Rafael Stubs Parpinelli

Sheila Cristiana De Freitas

Expert Syst. Appl., 2022

A Survey on Concept Drift in Process Mining.

[BibT_eX]

[DOI]

Denise Maria Vecino Sato

Roberto Souto Maior de Barros

Edson Emílio Scalabrin

ACM Comput. Surv., 2022

Evaluating k-NN in the Classification of Data Streams with Concept Drift.

[BibT_eX]

[DOI]

Silas Garrido Teixeira de Carvalho Santos

CoRR, 2022

Hierarchical classification of data streams: a systematic literature review.

[BibT_eX]

[DOI]

Roger Robson dos Santos

Artif. Intell. Rev., 2022

Improving Data Stream Classification using Incremental Yeo-Johnson Power Transformation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2022

Pattern Spotting and Image Retrieval in Historical Documents using Deep Hashing.

[BibT_eX]

[DOI]

Alessandro L. Koerich

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2022

Automatic disease vector mosquitoes identification via hierarchical data stream classification.

[BibT_eX]

[DOI]

Proceedings of the SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25, 2022

Classifying Hierarchical Data Streams using Global Classifiers and Summarization Techniques.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2022

Assessing Batch and Online Learning for Delivery in Full and On Time Predictions.

[BibT_eX]

[DOI]

Adriano Alves de Lima

Márcie Venâncio Batista

Luiz Eduardo Soares de Oliveira

Danilo Sipoli Sanches

Proceedings of the International Joint Conference on Neural Networks, 2022

Evaluation of Self-taught Learning-based Representations for Facial Emotion Recognition.

[BibT_eX]

[DOI]

Bruna Rossetto Delazeri

Leonardo León Vera

Alessandro L. Koerich

Alceu S. Britto Jr.

Proceedings of the International Joint Conference on Neural Networks, 2022

Univariate Time Series Prediction using Data Stream Mining Algorithms and Temporal Dependence.

[BibT_eX]

[DOI]

Marcos Alberto Mochinski

João Gabriel Corrêa Krüger

Proceedings of the 14th International Conference on Agents and Artificial Intelligence, 2022

A Machine Learning Approach for School Dropout Prediction in Brazil.

[BibT_eX]

[DOI]

Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021

A case study of batch and incremental recommender systems in supermarket data under concept drifts and cold start.

[BibT_eX]

[DOI]

Antônio David Viniski

Humberto Vinicius Aparecido de Campos

Expert Syst. Appl., 2021

Adaptive Global k-Nearest Neighbors for Hierarchical Classification of Data Streams.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics, 2021

UKIRF: An Item Rejection Framework for Improving Negative Items Sampling in One-Class Collaborative Filtering.

[BibT_eX]

[DOI]

Antônio David Viniski

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

Dynamically Selected Ensemble for Data Stream Classification.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2021

Towards the Overcome of Performance Pitfalls in Data Stream Mining Tools.

[BibT_eX]

[DOI]

Marco Antonio Zanata Alves

Proceedings of the International Joint Conference on Neural Networks, 2021

Interactive Process Drift Detection Framework.

[BibT_eX]

[DOI]

Denise Maria Vecino Sato

Edson Emílio Scalabrin

Proceedings of the Artificial Intelligence and Soft Computing, 2021

Classifying Potentially Unbounded Hierarchical Data Streams with Incremental Gaussian Naive Bayes.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Systems - 10th Brazilian Conference, 2021

2020

Lessons learned from data stream classification applied to credit scoring.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2020

scikit-dyn2sel - A Dynamic Selection Framework for Data Streams.

[BibT_eX]

[DOI]

CoRR, 2020

Regularized and incremental decision trees for data streams.

[BibT_eX]

[DOI]

Ann. des Télécommunications, 2020

Improving Multiple Time Series Forecasting with Data Stream Mining Algorithms.

[BibT_eX]

[DOI]

Marcos Alberto Mochinski

Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

ADADRIFT: An Adaptive Learning Technique for Long-history Stream-based Recommender Systems.

[BibT_eX]

[DOI]

Eduardo Ferreira José

Paulo Ricardo Lisboa de Almeida

Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Combining Slow and Fast Learning for Improved Credit Scoring.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Naïve Approaches to Deal With Concept Drifts.

[BibT_eX]

[DOI]

Luiz S. Oliveira

Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics, 2020

Cost-sensitive learning for imbalanced data streams.

[BibT_eX]

[DOI]

Lucas Loezer

Jean Antonio Pereira Karax

Proceedings of the SAC '20: The 35th ACM/SIGAPP Symposium on Applied Computing, online event, [Brno, Czech Republic], March 30, 2020

An End-to-End Approach for Recognition of Modern and Historical Handwritten Numeral Strings.

[BibT_eX]

[DOI]

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Classifier Pool Generation based on a Two-level Diversity Approach.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019

Machine learning for streaming data: state of the art, challenges, and opportunities.

[BibT_eX]

[DOI]

SIGKDD Explor., 2019

Correction to: Adaptive random forests for evolving data stream classification.

[BibT_eX]

[DOI]

Mach. Learn., 2019

Boosting decision stumps for dynamic feature selection on data streams.

[BibT_eX]

[DOI]

Inf. Syst., 2019

Merit-guided dynamic feature selection filter for data streams.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2019

Decision tree-based feature ranking in concept drifting data streams.

[BibT_eX]

[DOI]

Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, 2019

Learning regularized hoeffding trees from data streams.

[BibT_eX]

[DOI]

Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, 2019

Vertical and Horizontal Partitioning in Data Stream Regression Ensembles.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2019

2018

Iterative subset selection for feature drifting data streams.

[BibT_eX]

[DOI]

Lanqin Yuan

Bernhard Pfahringer

Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 2018

Are fintechs really a hype? A machine learning-based polarity analysis of Brazilian posts on social media.

[BibT_eX]

[DOI]

Marina Ponestke Seara

Altair Olivo Santin

Luis Eduardo Boiko Ferreira

Proceedings of the 16th IEEE International Conference on Industrial Informatics, 2018

An Experimental Perspective on Sampling Methods for Imbalanced Learning From Financial Databases.

[BibT_eX]

[DOI]

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Adaptive random forests for data stream regression.

[BibT_eX]

[DOI]

Luis Eduardo Boiko Ferreira

Albert Bifet

Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

2017

Adaptive random forests for evolving data stream classification.

[BibT_eX]

[DOI]

Mach. Learn., 2017

A survey on feature drift adaptation: Definition, benchmark, challenges and future directions.

[BibT_eX]

[DOI]

J. Syst. Softw., 2017

A Survey on Ensemble Learning for Data Stream Classification.

[BibT_eX]

[DOI]

ACM Comput. Surv., 2017

Improving Credit Risk Prediction in Online Peer-to-Peer (P2P) Lending Using Imbalanced Learning Techniques.

[BibT_eX]

[DOI]

Luis Eduardo Boiko Ferreira

Proceedings of the 29th IEEE International Conference on Tools with Artificial Intelligence, 2017

2016

SNCStream<sup>+</sup>: Extending a high quality true anytime data stream clustering algorithm.

[BibT_eX]

[DOI]

Inf. Syst., 2016

On Dynamic Feature Weighting for Feature Drifting Data Streams.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Towards emotion-based reputation guessing learning agents.

[BibT_eX]

[DOI]

Jones Granatyr

Adriano Weihmayer Almeida

Adaiane Pereira dos Santos Granatyr

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Overcoming feature drifts via dynamic feature weighted k-nearest neighbor learning.

[BibT_eX]

[DOI]

Jones Granatyr

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

A benchmark of classifiers on feature drifting data streams.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

2015

Advances on Concept Drift Detection in Regression Tasks Using Social Networks Theory.

[BibT_eX]

[DOI]

Int. J. Nat. Comput. Res., 2015

Pairwise combination of classifiers for ensemble learning on data streams.

[BibT_eX]

[DOI]

Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015

SNCStream: a social network-based data stream clustering algorithm.

[BibT_eX]

[DOI]

Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015

A Survey on Feature Drift Adaptation.

[BibT_eX]

[DOI]

Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence, 2015

On the Discovery of Time Distance Constrained Temporal Association Rules.

[BibT_eX]

[DOI]

Deborah Ribeiro de Carvalho

Lourdes Zubieta

Proceedings of the Neural Information Processing - 22nd International Conference, 2015

A Complex Network-Based Anytime Data Stream Clustering Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing - 22nd International Conference, 2015

Analyzing the Impact of Feature Drifts in Streaming Learning.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing - 22nd International Conference, 2015

Applying Ensemble-based Online Learning Techniques on Crime Forecasting.

[BibT_eX]

[DOI]

Anderson José de Souza

Proceedings of the ICEIS 2015, 2015

2014

SFNClassifier: a scale-free social network method to handle concept drift.

[BibT_eX]

[DOI]