Jean Paul Barddal

Cited by

	All	Since 2018
Citations	1710	1636
h-index	16	14
i10-index	19	19

520

260

130

390

20152016201720182019202020212022202311 17 38 116 234 315 369 508 92

Co-authors

Fabrício EnembreckPontificia Universidade Católica do ParanáVerified email at ppgia.pucpr.br
Heitor Murilo GomesLecturer in AI, Victoria University of WellingtonVerified email at vuw.ac.nz
Albert BifetTélécom ParisTech & University of WaikatoVerified email at telecom-paristech.fr
Bernhard PfahringerProfessor of Computer Science, University of WaikatoVerified email at waikato.ac.nz
Alceu de Souza Britto JrProfessor of Computer Science, Pontifical Catholic University of ParanaVerified email at ppgia.pucpr.br
Jesse ReadÉcole PolytechniqueVerified email at polytechnique.edu
Talel AbdessalemTélécom Paris, Institut Polytechnique de ParisVerified email at telecom-paris.fr
Geoffrey HolmesUniversity of WaikatoVerified email at waikato.ac.nz
Luis Eduardo Boiko FerreiraUniversidade Federal do ParanáVerified email at inf.ufpr.br
Joao GamaProfessor, Faculty of Economics, University of Porto, and INESC TECVerified email at fep.up.pt
Eduardo TieppoIT Professor at Instituto Federal do Paraná (IFPR)Verified email at ifpr.edu.br
Luiz Eduardo S. OliveiraFederal University of Parana, Dept of InformaticsVerified email at ufpr.br
Denise Maria Vecino SatoInstituto Federal do ParanáVerified email at ifpr.edu.br
Edson Emilio ScalabrinPUCPRVerified email at ppgia.pucpr.br
Paulo Ricardo Lisboa de AlmeidaProfessor, Universidade Federal do ParanáVerified email at ufpr.br
Robert SabourinProfessor emeritus @ École de technologie supérieure - LIVIA - REPARTIVerified email at etsmtl.ca
Andreia MalucelliProfessor of Computer Science, Pontifical Catholic University of ParanáVerified email at ppgia.pucpr.br
Lanqin YuanUniversity of Technology SydneyVerified email at student.uts.edu.au
ANTONIO DAVID VINISKIPontifícia Universidade Católica do ParanáVerified email at ppgia.pucpr.br
Jeovane Honório AlvesPhD in Computer Science, Federal University of ParanaVerified email at inf.ufpr.br

Jean Paul Barddal

Programa de Pós-Graduação em Informática (PPGIa), Pontifícia Universidade Católica do Paraná

Verified email at ppgia.pucpr.br - Homepage

Machine Learning Data Stream Mining Big Data


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Adaptive random forests for evolving data stream classification HM Gomes, A Bifet, J Read, JP Barddal, F Enembreck, B Pfharinger, ... Machine Learning 106, 1469-1495, 2017	520	2017
A survey on ensemble learning for data stream classification HM Gomes, JP Barddal, F Enembreck, A Bifet ACM Computing Surveys (CSUR) 50 (2), 1-36, 2017	451	2017
Machine learning for streaming data: state of the art, challenges, and opportunities HM Gomes, J Read, A Bifet, JP Barddal, J Gama ACM SIGKDD Explorations Newsletter 21 (2), 6-22, 2019	159*	2019
A survey on feature drift adaptation: Definition, benchmark, challenges and future directions JP Barddal, HM Gomes, F Enembreck, B Pfahringer Journal of Systems and Software 127, 278-294, 2017	93	2017
Adaptive random forests for data stream regression. HM Gomes, JP Barddal, LEB Ferreira, A Bifet ESANN, 2018	44	2018
On dynamic feature weighting for feature drifting data streams JP Barddal, H Murilo Gomes, F Enembreck, B Pfahringer, A Bifet Machine Learning and Knowledge Discovery in Databases: European Conference …, 2016	39	2016
A survey on concept drift in process mining DMV Sato, SC De Freitas, JP Barddal, EE Scalabrin ACM Computing Surveys (CSUR) 54 (9), 1-38, 2021	31	2021
Lessons learned from data stream classification applied to credit scoring JP Barddal, L Loezer, F Enembreck, R Lanzuolo Expert Systems with Applications 162, 113899, 2020	31	2020
SNCStream: a social network-based data stream clustering algorithm JP Barddal, HM Gomes, F Enembreck Proceedings of the 30th annual ACM symposium on applied computing, 935-940, 2015	31	2015
Improving credit risk prediction in online peer-to-peer (p2p) lending using imbalanced learning techniques LEB Ferreira, JP Barddal, HM Gomes, F Enembreck 2017 IEEE 29th International Conference on Tools with Artificial …, 2017	26	2017
A survey on feature drift adaptation JP Barddal, HM Gomes, F Enembreck 2015 IEEE 27th International Conference on Tools with Artificial …, 2015	26	2015
SFNClassifier: A scale-free social network method to handle concept drift JP Barddal, HM Gomes, F Enembreck Proceedings of the 29th Annual ACM Symposium on Applied Computing, 786-791, 2014	26	2014
Boosting decision stumps for dynamic feature selection on data streams JP Barddal, F Enembreck, HM Gomes, A Bifet, B Pfahringer Information Systems 83, 13-29, 2019	25	2019
Merit-guided dynamic feature selection filter for data streams JP Barddal, F Enembreck, HM Gomes, A Bifet, B Pfahringer Expert Systems with Applications 116, 227-242, 2019	24	2019
SNCStream+: Extending a high quality true anytime data stream clustering algorithm JP Barddal, HM Gomes, F Enembreck, JP Barthès Information Systems 62, 60-73, 2016	21	2016
Analyzing the impact of feature drifts in streaming learning JP Barddal, HM Gomes, F Enembreck Neural Information Processing: 22nd International Conference, ICONIP 2015 …, 2015	20	2015
Cost-sensitive learning for imbalanced data streams L Loezer, F Enembreck, JP Barddal, A de Souza Britto Jr Proceedings of the 35th annual ACM symposium on applied computing, 498-504, 2020	13	2020
A case study of batch and incremental recommender systems in supermarket data under concept drifts and cold start AD Viniski, JP Barddal, A de Souza Britto Jr, F Enembreck, ... Expert Systems with Applications 176, 114890, 2021	11	2021
Learning regularized hoeffding trees from data streams JP Barddal, F Enembreck Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, 574-581, 2019	10	2019
Hierarchical classification of data streams: a systematic literature review E Tieppo, RR Santos, JP Barddal, JC Nievola Artificial Intelligence Review, 1-40, 2022	9	2022

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