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Journal Articles
- 2024
[j8]Eduardo Tieppo
, Júlio César Nievola, Jean Paul Barddal:
Adaptive learning on hierarchical data streams using window-weighted Gaussian probabilities. Appl. Soft Comput. 152: 111271 (2024)- [j7]Luiz Rafael Schmitke, Emerson Cabrera Paraiso, Júlio César Nievola:
Biclustering-based multi-label classification. Knowl. Inf. Syst. 66(8): 4861-4898 (2024) - 2022
- [j6]Eduardo Tieppo, Roger Robson dos Santos, Jean Paul Barddal, Júlio César Nievola:
Hierarchical classification of data streams: a systematic literature review. Artif. Intell. Rev. 55(4): 3243-3282 (2022) - 2021
- [j5]Elias Cesar Araujo De Carvalho, Joao Ricardo Nickenig Vissoci, Luciano de Andrade, Wagner de Lara Machado, Emerson Cabrera Paraiso, Júlio César Nievola:
BNPA: An R package to learn path analysis input models from a data set semi-automatically using Bayesian networks. Knowl. Based Syst. 223: 107042 (2021) - 2015
- [j4]Cecilia H. Vallejos de Schatz, Fabio Kurt Schneider, Paulo José Abatti, Júlio C. Nievola:
Dynamic Fuzzy-Neural based tool formonitoring and predicting patients conditions using selected vital signs. J. Intell. Fuzzy Syst. 28(6): 2579-2590 (2015) - 2013
- [j3]Helyane Bronoski Borges, Carlos Nascimento Silla Jr., Júlio César Nievola:
An evaluation of global-model hierarchical classification algorithms for hierarchical classification problems with single path of labels. Comput. Math. Appl. 66(10): 1991-2002 (2013) - 2012
- [j2]P. S. M. Nizer, Júlio C. Nievola:
Predicting published news effect in the Brazilian stock market. Expert Syst. Appl. 39(12): 10674-10680 (2012) - [j1]Helyane Bronoski Borges, Júlio C. Nievola:
Comparing the dimensionality reduction methods in gene expression databases. Expert Syst. Appl. 39(12): 10780-10795 (2012)
Conference and Workshop Papers
- 2022
- [c49]Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola:
Classifying Hierarchical Data Streams using Global Classifiers and Summarization Techniques. IJCNN 2022: 1-8 - [c48]Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola:
Automatic disease vector mosquitoes identification via hierarchical data stream classification. SAC 2022: 1005-1012 - [c47]Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola:
Improving Data Stream Classification using Incremental Yeo-Johnson Power Transformation. SMC 2022: 3286-3292 - 2021
- [c46]Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola:
Classifying Potentially Unbounded Hierarchical Data Streams with Incremental Gaussian Naive Bayes. BRACIS (1) 2021: 421-436 - [c45]Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola:
Adaptive Global k-Nearest Neighbors for Hierarchical Classification of Data Streams. SMC 2021: 631-636 - 2019
- [c44]Luiz Bernardo Martins Kummer, Hiroyuki Iida, Júlio César Nievola, Emerson Cabrera Paraiso:
Identifying Influences of Game Upgrades on Profitable Players Behavior in MMORPGs. ICEC-JCSG 2019: 299-310 - 2018
- [c43]Luiz Bernardo Martins Kummer, Júlio César Nievola, Emerson Cabrera Paraiso:
Applying Commitment to Churn and Remaining Players Lifetime Prediction. CIG 2018: 1-8 - [c42]Luiz Bernardo Martins Kummer, Júlio César Nievola, Emerson Cabrera Paraiso:
Identifying Niche Stage in MMORPGs Using Ensemble Classifier. FLAIRS 2018: 288-293 - [c41]Wendel Góes Pedrozo, Júlio César Nievola, Deborah Ribeiro Carvalho:
An Adaptive Approach for Index Tuning with Learning Classifier Systems on Hybrid Storage Environments. HAIS 2018: 716-729 - [c40]Luiz H. F. Giovanini, Elisangela F. Manffra, Júlio C. Nievola:
Discriminating Postural Control Behaviors from Posturography with Statistical Tests and Machine Learning Models: Does Time Series Length Matter? ICCS (3) 2018: 350-357 - [c39]Norberto Ritzmann Junior, Júlio César Nievola:
A generalized financial time series forecasting model based on automatic feature engineering using genetic algorithms and support vector machine. IJCNN 2018: 1-8 - 2017
- [c38]Rodolfo Garcia, Emerson Cabrera Paraiso, Júlio César Nievola:
Comparative Study of Dimensionality Reduction Methods Using Reliable Features for Multiple Datasets Obtained by rs-fMRI in ADHD Prediction. Canadian AI 2017: 97-102 - [c37]Luiz Kummer, Júlio C. Nievola, Emerson Cabrera Paraiso:
A Key Risk Indicator for the Game Usage Lifecycle. FLAIRS 2017: 394-399 - [c36]Luiz Henrique Franco Giovanini, Simone M. Silva, Elisangela F. Manffra, Júlio C. Nievola:
Sampling and Digital Filtering Effects When Recognizing Postural Control with Statistical Tools and the Decision Tree Classifier. ICCS 2017: 129-138 - [c35]Alex Meincheim, Cleiton dos Santos Garcia, Júlio César Nievola, Edson Emílio Scalabrin:
Combining Process Mining with Trace Clustering: Manufacturing Shop Floor Process - An Applied Case. ICTAI 2017: 498-505 - 2016
- [c34]Marcus Vinícius Mazega Figueredo, Emerson Cabrera Paraiso, Júlio César Nievola:
A constructive algorithm for neural networks inspired on decision trees and evolutionary algorithms. IJCNN 2016: 1120-1127 - [c33]Marcelo J. Cossetin, Júlio C. Nievola, Alessandro L. Koerich:
Facial expression recognition using a pairwise feature selection and classification approach. IJCNN 2016: 5149-5155 - 2015
- [c32]Júlio César Nievola, Emerson Cabrera Paraiso, Alex Alves Freitas:
A hierarchical neural network for predicting protein functions. BIBE 2015: 1-5 - [c31]Luiz Melo Romão, Júlio César Nievola:
Hierarchical Multi-label Classification Problems: An LCS Approach. DCAI 2015: 97-104 - [c30]Luiz Henrique Giovanini Marrega, Simone M. Silva, Elisangela F. Manffra, Júlio C. Nievola:
Comparison between Decision Tree and Genetic Programming to distinguish healthy from stroke postural sway patterns. EMBC 2015: 6820-6823 - [c29]Lohann Ferreira, Mariza Dosciatti, Júlio C. Nievola, Emerson Cabrera Paraiso:
Using a Genetic Algorithm Approach to Study the Impact of Imbalanced Corpora in Sentiment Analysis. FLAIRS 2015: 163-168 - [c28]Mauri Ferrandin, Fabrício Enembreck, Júlio César Nievola, Edson Emílio Scalabrin, Bráulio Coelho Ávila:
A Centroid-based Approach for Hierarchical Classification. ICEIS (1) 2015: 25-33 - 2014
- [c27]Rafael Abud Menezes, Júlio César Nievola:
RCMDE-GMD: Predicting gene ontology terms using differential evolution. FSKD 2014: 518-524 - [c26]Luiz Henrique Giovanini Marrega, Júlio César Nievola:
Evaluation of the Relevance of Linear and Nonlinear Posturographic Features in the Recognition of Healthy Subjects and Stroke Patients. ICDM Workshops 2014: 111-118 - 2013
- [c25]Lucas Galete, Milton Pires Ramos, Júlio César Nievola, Emerson Cabrera Paraiso:
Dynamically modeling users with MODUS-SD and Kohonen's map. CSCWD 2013: 17-22 - 2012
- [c24]Luiz Melo Romão, Júlio C. Nievola:
Predicting GPCR and enzymes function with a global approach based on LCS. BIBE 2012: 151-156 - [c23]Luiz Melo Romão, Júlio C. Nievola:
Hierarchical Classification of Gene Ontology with Learning Classifier Systems. IBERAMIA 2012: 120-129 - [c22]Helyane Bronoski Borges, Júlio C. Nievola:
Hierarchical classification using a Competitive Neural Network. ICNC 2012: 172-177 - [c21]Helyane Bronoski Borges, Júlio C. Nievola:
Multi-Label Hierarchical Classification using a Competitive Neural Network for protein function prediction. IJCNN 2012: 1-8 - [c20]Marcio L. F. Miguel, Manoel Camillo Penna, Júlio C. Nievola, Marcelo Eduardo Pellenz:
New models for long-term Internet traffic forecasting using artificial neural networks and flow based information. NOMS 2012: 1082-1088 - 2011
- [c19]G. Boz, Milton Pires Ramos, Gilson Yukio Sato, Júlio C. Nievola, Emerson Cabrera Paraiso:
Noctua: A tool for Knowledge Acquisition and Collaborative Knowledge Construction with a virtual catalyst. CSCWD 2011: 222-229 - [c18]Rodolfo Garcia, Emerson Cabrera Paraiso, Júlio C. Nievola:
Multiobjective Optimization of Indexes Obtained by Clustering for Feature Selection Methods Evaluation in Genes Expression Microarrays. IDEAL 2011: 353-360 - [c17]Priscila Vriesman Araujo, Carlos Alberto Maziero, Júlio César Nievola:
Automatic Classification of Processes in a General-Purpose Operating System. SBESC 2011: 33-38 - [c16]Geraldo Boz Jr., Milton Pires Ramos, Gilson Yukio Sato, Cesar Augusto Tacla, Júlio C. Nievola, Emerson Cabrera Paraiso:
A Virtual Catalyst in the Knowledge Acquisition Process. SEKE 2011: 149-152 - 2009
- [c15]Helyane Bronoski Borges, Júlio C. Nievola:
Dimensionality Reduction in Gene Expression Database through the Random Projection Method. ICMLA 2009: 557-562 - 2008
- [c14]Thiago Bassani, Júlio C. Nievola:
Pattern recognition for brain-computer interface on disabled subjects using a wavelet transformation. CIBCB 2008: 180-186 - [c13]Euclides Peres Farias, Júlio C. Nievola:
Comparative of data base evolution in rule association algorithms in incremental and conventional way. IJCNN 2008: 3131-3137 - 2007
- [c12]Helyane Bronoski Borges, Júlio C. Nievola:
Gene-finding as an Attribute Selection Task. ACIS-ICIS 2007: 537-542 - [c11]Daniele Yumi Sunaga, Júlio C. Nievola, Milton Pires Ramos:
Statistical and Biological Validation Methods in Cluster Analysis of Gene Expression. ICMLA 2007: 494-499 - [c10]Helyane Bronoski Borges, Júlio C. Nievola:
Feature Selection as a Preprocessing Step for Classification in Gene Expression Data. ISDA 2007: 157-162 - 2006
- [c9]Vera Lucia M. Falquete, Júlio C. Nievola, Celso A. A. Kaestner:
Automatic Inconsistency Treatment in Case-Based Reasoning Systems. SBBD 2006: 31-41 - 2005
- [c8]Júlio C. Nievola, Helyane Bronoski Borges:
Attribute selection methods comparison for classification of diffuse large B-cell lymphoma. ICMLA 2005 - 2003
- [c7]Fernando E. B. Otero, Monique M. S. Silva, Alex Alves Freitas, Júlio C. Nievola:
Genetic Programming for Attribute Construction in Data Mining. EuroGP 2003: 384-393 - [c6]Marcelo N. Kapp, Cinthia Obladen de Almendra Freitas, Júlio C. Nievola, Robert Sabourin:
Evaluating the Conventional and Class-Modular Architectures Feedforward Neural Network for Handwritten Word Recognition. SIBGRAPI 2003: 315-322 - 2002
- [c5]Otavio Larsen, Alex Alves Freitas, Júlio C. Nievola:
Constructing X-of-N Attributes with a Genetic Algorithm. GECCO Late Breaking Papers 2002: 316-322 - [c4]Otavio Larsen, Alex Alves Freitas, Júlio C. Nievola:
Constructing X-of-n Attributes With A Genetic Algorithm. GECCO 2002: 1268 - 2001
- [c3]Roberto R. F. Mendes, Fabricio de B. Voznika, Alex Alves Freitas, Júlio C. Nievola:
Discovering Fuzzy Classification Rules with Genetic Programming and Co-evolution. PKDD 2001: 314-325 - 1999
- [c2]Monika Koncke Fiuza Parolin, Júlio C. Nievola:
Tutor Based on Simulation for Trauma Medical Training in Pre-Hospital Care. Applied Informatics 1999: 212-214 - [c1]Lucimar F. de Carvalho, Hugo J. T. de Carvalho, Júlio C. Nievola, Celso A. A. Kaestner, Christiane Koehler, Charles T. Batezini, Raquele Z. Grazziotin, Vinícius S. Borguetti:
Expert System Object-Oriented Combining Systematic and Heuristic Reasoning. ICEIS 1999: 763
Parts in Books or Collections
- 2009
- [p2]Helyane Bronoski Borges, Júlio C. Nievola:
Gene Selection from Microarray Data. Intelligent Text Categorization and Clustering 2009: 1-23 - 2008
- [p1]Marcus Vinícius Mazega Figueredo, Júlio C. Nievola, Sérgio Renato Rogal, Alfredo Beckert Neto:
Compression of Electrocardiogram Using Neural Networks and Wavelets. Computer and Information Science 2008: 27-40
Informal and Other Publications
- 2018
- [i1]Norberto Ritzmann Junior, Júlio César Nievola:
A generalized financial time series forecasting model based on automatic feature engineering using genetic algorithms and support vector machine. CoRR abs/1809.06775 (2018)
Coauthor Index
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