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Artigo de periodico
Dataset: annotated soybean market news articles (2024)
Reis Filho, Ivan José dos ; Coleti, Jamille de Campos; Marcacini, Ricardo Marcondes ; Rezende, Solange Oliveira
Source: Data in Brief. Unidade: ICMC
Subjects: MINERAÇÃO DE DADOS, PROCESSAMENTO DE LINGUAGEM NATURAL, MERCADO AGRÍCOLA
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ABNT
REIS FILHO, Ivan José dos et al. Dataset: annotated soybean market news articles. Data in Brief, v. 55, p. 1-9, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.dib.2024.110545. Acesso em: 16 out. 2024.
APA
Reis Filho, I. J. dos, Coleti, J. de C., Marcacini, R. M., & Rezende, S. O. (2024). Dataset: annotated soybean market news articles. Data in Brief, 55, 1-9. doi:10.1016/j.dib.2024.110545
NLM
Reis Filho IJ dos, Coleti J de C, Marcacini RM, Rezende SO. Dataset: annotated soybean market news articles [Internet]. Data in Brief. 2024 ; 55 1-9.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.dib.2024.110545
Vancouver
Reis Filho IJ dos, Coleti J de C, Marcacini RM, Rezende SO. Dataset: annotated soybean market news articles [Internet]. Data in Brief. 2024 ; 55 1-9.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.dib.2024.110545
Artigo de periodico
Detecting relevant app reviews for software evolution and maintenance through multimodal one-class learning (2022)
Gôlo, Marcos Paulo Silva ; Araujo, Adailton Ferreira de ; Rossi, Rafael Geraldeli ; Marcacini, Ricardo Marcondes
Source: Information and Software Technology. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS, RECONHECIMENTO DE TEXTO, DESENVOLVIMENTO DE SOFTWARE
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ABNT
GÔLO, Marcos Paulo Silva et al. Detecting relevant app reviews for software evolution and maintenance through multimodal one-class learning. Information and Software Technology, v. No 2022, p. 1-12, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.infsof.2022.106998. Acesso em: 16 out. 2024.
APA
Gôlo, M. P. S., Araujo, A. F. de, Rossi, R. G., & Marcacini, R. M. (2022). Detecting relevant app reviews for software evolution and maintenance through multimodal one-class learning. Information and Software Technology, No 2022, 1-12. doi:10.1016/j.infsof.2022.106998
NLM
Gôlo MPS, Araujo AF de, Rossi RG, Marcacini RM. Detecting relevant app reviews for software evolution and maintenance through multimodal one-class learning [Internet]. Information and Software Technology. 2022 ; No 2022 1-12.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.infsof.2022.106998
Vancouver
Gôlo MPS, Araujo AF de, Rossi RG, Marcacini RM. Detecting relevant app reviews for software evolution and maintenance through multimodal one-class learning [Internet]. Information and Software Technology. 2022 ; No 2022 1-12.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.infsof.2022.106998
Artigo de periodico
On the enrichment of time series with textual data for forecasting agricultural commodity prices (2022)
Reis Filho, Ivan José ; Marcacini, Ricardo Marcondes ; Rezende, Solange Oliveira
Source: MethodsX. Unidade: ICMC
Subjects: MINERAÇÃO DE DADOS, APRENDIZADO COMPUTACIONAL, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS)
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ABNT
REIS FILHO, Ivan José e MARCACINI, Ricardo Marcondes e REZENDE, Solange Oliveira. On the enrichment of time series with textual data for forecasting agricultural commodity prices. MethodsX, v. 9, p. 1-11, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.mex.2022.101758. Acesso em: 16 out. 2024.
APA
Reis Filho, I. J., Marcacini, R. M., & Rezende, S. O. (2022). On the enrichment of time series with textual data for forecasting agricultural commodity prices. MethodsX, 9, 1-11. doi:10.1016/j.mex.2022.101758
NLM
Reis Filho IJ, Marcacini RM, Rezende SO. On the enrichment of time series with textual data for forecasting agricultural commodity prices [Internet]. MethodsX. 2022 ; 9 1-11.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.mex.2022.101758
Vancouver
Reis Filho IJ, Marcacini RM, Rezende SO. On the enrichment of time series with textual data for forecasting agricultural commodity prices [Internet]. MethodsX. 2022 ; 9 1-11.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.mex.2022.101758
Artigo de periodico
Challenges in benchmarking stream learning algorithms with real-world data (2020)
Souza, Vinícius Mourão Alves de ; Reis, Denis Moreira dos ; Maletzke, André Gustavo ; Batista, Gustavo Enrique de Almeida Prado Alves
Source: Data Mining and Knowledge Discovery. Unidade: ICMC
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, MINERAÇÃO DE DADOS, ALGORITMOS ÚTEIS E ESPECÍFICOS, BENCHMARKS
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ABNT
SOUZA, Vinícius Mourão Alves de et al. Challenges in benchmarking stream learning algorithms with real-world data. Data Mining and Knowledge Discovery, v. No 2020, n. 6, p. 1805-1858, 2020Tradução . . Disponível em: https://doi.org/10.1007/s10618-020-00698-5. Acesso em: 16 out. 2024.
APA
Souza, V. M. A. de, Reis, D. M. dos, Maletzke, A. G., & Batista, G. E. de A. P. A. (2020). Challenges in benchmarking stream learning algorithms with real-world data. Data Mining and Knowledge Discovery, No 2020( 6), 1805-1858. doi:10.1007/s10618-020-00698-5
NLM
Souza VMA de, Reis DM dos, Maletzke AG, Batista GE de APA. Challenges in benchmarking stream learning algorithms with real-world data [Internet]. Data Mining and Knowledge Discovery. 2020 ; No 2020( 6): 1805-1858.[citado 2024 out. 16 ] Available from: https://doi.org/10.1007/s10618-020-00698-5
Vancouver
Souza VMA de, Reis DM dos, Maletzke AG, Batista GE de APA. Challenges in benchmarking stream learning algorithms with real-world data [Internet]. Data Mining and Knowledge Discovery. 2020 ; No 2020( 6): 1805-1858.[citado 2024 out. 16 ] Available from: https://doi.org/10.1007/s10618-020-00698-5
Artigo de periodico
Unsupervised dimensionality reduction for very large datasets: are we going to the right direction? (2020)
Oliveira, Jadson José Monteiro ; Cordeiro, Robson Leonardo Ferreira
Source: Knowledge-Based Systems. Unidade: ICMC
Subjects: BANCO DE DADOS, MINERAÇÃO DE DADOS, FRACTAIS
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ABNT
OLIVEIRA, Jadson José Monteiro e CORDEIRO, Robson Leonardo Ferreira. Unsupervised dimensionality reduction for very large datasets: are we going to the right direction?. Knowledge-Based Systems, v. 196, p. 1-14, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2020.105777. Acesso em: 16 out. 2024.
APA
Oliveira, J. J. M., & Cordeiro, R. L. F. (2020). Unsupervised dimensionality reduction for very large datasets: are we going to the right direction? Knowledge-Based Systems, 196, 1-14. doi:10.1016/j.knosys.2020.105777
NLM
Oliveira JJM, Cordeiro RLF. Unsupervised dimensionality reduction for very large datasets: are we going to the right direction? [Internet]. Knowledge-Based Systems. 2020 ; 196 1-14.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.knosys.2020.105777
Vancouver
Oliveira JJM, Cordeiro RLF. Unsupervised dimensionality reduction for very large datasets: are we going to the right direction? [Internet]. Knowledge-Based Systems. 2020 ; 196 1-14.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.knosys.2020.105777
Artigo de periodico
Unsupervised learning of textual pattern based on propagation in bipartite graph (2020)
Faleiros, Thiago de Paulo; Valejo, Alan Demetrius Baria ; Lopes, Alneu de Andrade
Source: Intelligent Data Analysis. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS
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ABNT
FALEIROS, Thiago de Paulo e VALEJO, Alan Demetrius Baria e LOPES, Alneu de Andrade. Unsupervised learning of textual pattern based on propagation in bipartite graph. Intelligent Data Analysis, v. 24, n. 3, p. 543-565, 2020Tradução . . Disponível em: https://doi.org/10.3233/IDA-194528. Acesso em: 16 out. 2024.
APA
Faleiros, T. de P., Valejo, A. D. B., & Lopes, A. de A. (2020). Unsupervised learning of textual pattern based on propagation in bipartite graph. Intelligent Data Analysis, 24( 3), 543-565. doi:10.3233/IDA-194528
NLM
Faleiros T de P, Valejo ADB, Lopes A de A. Unsupervised learning of textual pattern based on propagation in bipartite graph [Internet]. Intelligent Data Analysis. 2020 ; 24( 3): 543-565.[citado 2024 out. 16 ] Available from: https://doi.org/10.3233/IDA-194528
Vancouver
Faleiros T de P, Valejo ADB, Lopes A de A. Unsupervised learning of textual pattern based on propagation in bipartite graph [Internet]. Intelligent Data Analysis. 2020 ; 24( 3): 543-565.[citado 2024 out. 16 ] Available from: https://doi.org/10.3233/IDA-194528
Trabalho de evento-anais periodico
Compressed k-nearest neighbors ensembles for evolving data streams (2020)
Bahri, Maroua ; Bifet, Albert ; Maniu, Silviu ; Mello, Rodrigo Fernandes de ; Tziortziotis, Nikolaos
Source: Frontiers in Artificial Intelligence and Applications. Conference titles: European Conference on Artificial Intelligence - ECAI. Unidade: ICMC
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS, ALGORITMOS ÚTEIS E ESPECÍFICOS
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ABNT
BAHRI, Maroua et al. Compressed k-nearest neighbors ensembles for evolving data streams. Frontiers in Artificial Intelligence and Applications. Amsterdam: IOS Press. Disponível em: https://doi.org/10.3233/FAIA200189. Acesso em: 16 out. 2024. , 2020
APA
Bahri, M., Bifet, A., Maniu, S., Mello, R. F. de, & Tziortziotis, N. (2020). Compressed k-nearest neighbors ensembles for evolving data streams. Frontiers in Artificial Intelligence and Applications. Amsterdam: IOS Press. doi:10.3233/FAIA200189
NLM
Bahri M, Bifet A, Maniu S, Mello RF de, Tziortziotis N. Compressed k-nearest neighbors ensembles for evolving data streams [Internet]. Frontiers in Artificial Intelligence and Applications. 2020 ; 325 961-968.[citado 2024 out. 16 ] Available from: https://doi.org/10.3233/FAIA200189
Vancouver
Bahri M, Bifet A, Maniu S, Mello RF de, Tziortziotis N. Compressed k-nearest neighbors ensembles for evolving data streams [Internet]. Frontiers in Artificial Intelligence and Applications. 2020 ; 325 961-968.[citado 2024 out. 16 ] Available from: https://doi.org/10.3233/FAIA200189
Artigo de periodico
Knowledge-enhanced document embeddings for text classification (2019)
Sinoara, Roberta Akemi; Camacho-Collados, Jose; Rossi, Rafael G; Navigli, Roberto; Rezende, Solange Oliveira
Source: Knowledge-Based Systems. Unidade: ICMC
Subjects: MINERAÇÃO DE DADOS, RECONHECIMENTO DE TEXTO
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ABNT
SINOARA, Roberta Akemi et al. Knowledge-enhanced document embeddings for text classification. Knowledge-Based Systems, v. 163, n. Ja 2019, p. 955-971, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2018.10.026. Acesso em: 16 out. 2024.
APA
Sinoara, R. A., Camacho-Collados, J., Rossi, R. G., Navigli, R., & Rezende, S. O. (2019). Knowledge-enhanced document embeddings for text classification. Knowledge-Based Systems, 163( Ja 2019), 955-971. doi:10.1016/j.knosys.2018.10.026
NLM
Sinoara RA, Camacho-Collados J, Rossi RG, Navigli R, Rezende SO. Knowledge-enhanced document embeddings for text classification [Internet]. Knowledge-Based Systems. 2019 ; 163( Ja 2019): 955-971.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.knosys.2018.10.026
Vancouver
Sinoara RA, Camacho-Collados J, Rossi RG, Navigli R, Rezende SO. Knowledge-enhanced document embeddings for text classification [Internet]. Knowledge-Based Systems. 2019 ; 163( Ja 2019): 955-971.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.knosys.2018.10.026
Artigo de periodico
Empirical investigation of active learning strategies (2019)
Pereira-Santos, Davi; Prudêncio, Ricardo Bastos Cavalcante; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Neurocomputing. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS, RECONHECIMENTO DE PADRÕES
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ABNT
PEREIRA-SANTOS, Davi e PRUDÊNCIO, Ricardo Bastos Cavalcante e CARVALHO, André Carlos Ponce de Leon Ferreira de. Empirical investigation of active learning strategies. Neurocomputing, v. 326-327, n. Ja 2019, p. 15-27, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2017.05.105. Acesso em: 16 out. 2024.
APA
Pereira-Santos, D., Prudêncio, R. B. C., & Carvalho, A. C. P. de L. F. de. (2019). Empirical investigation of active learning strategies. Neurocomputing, 326-327( Ja 2019), 15-27. doi:10.1016/j.neucom.2017.05.105
NLM
Pereira-Santos D, Prudêncio RBC, Carvalho ACP de LF de. Empirical investigation of active learning strategies [Internet]. Neurocomputing. 2019 ; 326-327( Ja 2019): 15-27.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.neucom.2017.05.105
Vancouver
Pereira-Santos D, Prudêncio RBC, Carvalho ACP de LF de. Empirical investigation of active learning strategies [Internet]. Neurocomputing. 2019 ; 326-327( Ja 2019): 15-27.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.neucom.2017.05.105
Artigo de periodico
Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs (2017)
Faleiros, Thiago de Paulo; Rossi, Rafael Geraldeli; Lopes, Alneu de Andrade
Source: Pattern Recognition Letters. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS
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ABNT
FALEIROS, Thiago de Paulo e ROSSI, Rafael Geraldeli e LOPES, Alneu de Andrade. Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs. Pattern Recognition Letters, v. 87, p. 127-138, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.patrec.2016.04.006. Acesso em: 16 out. 2024.
APA
Faleiros, T. de P., Rossi, R. G., & Lopes, A. de A. (2017). Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs. Pattern Recognition Letters, 87, 127-138. doi:10.1016/j.patrec.2016.04.006
NLM
Faleiros T de P, Rossi RG, Lopes A de A. Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs [Internet]. Pattern Recognition Letters. 2017 ; 87 127-138.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.patrec.2016.04.006
Vancouver
Faleiros T de P, Rossi RG, Lopes A de A. Optimizing the class information divergence for transductive classification of texts using propagation in bipartite graphs [Internet]. Pattern Recognition Letters. 2017 ; 87 127-138.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.patrec.2016.04.006
Artigo de periodico
Improving k-means through distributed scalable metaheuristics (2017)
Oliveira, G. V; Coutinho, F. P; Campello, Ricardo José Gabrielli Barreto; Naldi, M. C
Source: Neurocomputing. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, ALGORITMOS, MINERAÇÃO DE DADOS, HEURÍSTICA, ALGORITMOS GENÉTICOS
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ABNT
OLIVEIRA, G. V et al. Improving k-means through distributed scalable metaheuristics. Neurocomputing, v. 246, p. 45-57, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2016.07.074. Acesso em: 16 out. 2024.
APA
Oliveira, G. V., Coutinho, F. P., Campello, R. J. G. B., & Naldi, M. C. (2017). Improving k-means through distributed scalable metaheuristics. Neurocomputing, 246, 45-57. doi:10.1016/j.neucom.2016.07.074
NLM
Oliveira GV, Coutinho FP, Campello RJGB, Naldi MC. Improving k-means through distributed scalable metaheuristics [Internet]. Neurocomputing. 2017 ; 246 45-57.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.neucom.2016.07.074
Vancouver
Oliveira GV, Coutinho FP, Campello RJGB, Naldi MC. Improving k-means through distributed scalable metaheuristics [Internet]. Neurocomputing. 2017 ; 246 45-57.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.neucom.2016.07.074
Artigo de periodico
Patterns of authors contribution in scientific manuscripts (2017)
Corrêa Jr., Edilson A.; Silva, Filipi N.; Costa, Luciano da Fontoura ; Amancio, Diego Raphael
Source: Journal of Informetrics. Unidades: IFSC, ICMC
Subjects: ENTROPIA, MINERAÇÃO DE DADOS, RECONHECIMENTO DE PADRÕES
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ABNT
CORRÊA JR., Edilson A. et al. Patterns of authors contribution in scientific manuscripts. Journal of Informetrics, v. 11, n. 2, p. 498-510, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.joi.2017.03.003. Acesso em: 16 out. 2024.
APA
Corrêa Jr., E. A., Silva, F. N., Costa, L. da F., & Amancio, D. R. (2017). Patterns of authors contribution in scientific manuscripts. Journal of Informetrics, 11( 2), 498-510. doi:10.1016/j.joi.2017.03.003
NLM
Corrêa Jr. EA, Silva FN, Costa L da F, Amancio DR. Patterns of authors contribution in scientific manuscripts [Internet]. Journal of Informetrics. 2017 ; 11( 2): 498-510.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.joi.2017.03.003
Vancouver
Corrêa Jr. EA, Silva FN, Costa L da F, Amancio DR. Patterns of authors contribution in scientific manuscripts [Internet]. Journal of Informetrics. 2017 ; 11( 2): 498-510.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.joi.2017.03.003
Artigo de periodico
Mining unstructured content for recommender systems: an ensemble approach (2016)
Manzato, Marcelo Garcia ; Domingues, Marcos A; Fortes, Arthur C; Sundermann, Camila V; D'Addio, Rafael M; Conrado, Merley S; Rezende, Solange Oliveira ; Pimentel, Maria da Graça Campos
Source: Information Retrieval Journal. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS, RECONHECIMENTO DE TEXTO, WORLD WIDE WEB
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ABNT
MANZATO, Marcelo Garcia et al. Mining unstructured content for recommender systems: an ensemble approach. Information Retrieval Journal, v. 19, n. 4, p. 378-415, 2016Tradução . . Disponível em: https://doi.org/10.1007/s10791-016-9280-8. Acesso em: 16 out. 2024.
APA
Manzato, M. G., Domingues, M. A., Fortes, A. C., Sundermann, C. V., D'Addio, R. M., Conrado, M. S., et al. (2016). Mining unstructured content for recommender systems: an ensemble approach. Information Retrieval Journal, 19( 4), 378-415. doi:10.1007/s10791-016-9280-8
NLM
Manzato MG, Domingues MA, Fortes AC, Sundermann CV, D'Addio RM, Conrado MS, Rezende SO, Pimentel M da GC. Mining unstructured content for recommender systems: an ensemble approach [Internet]. Information Retrieval Journal. 2016 ; 19( 4): 378-415.[citado 2024 out. 16 ] Available from: https://doi.org/10.1007/s10791-016-9280-8
Vancouver
Manzato MG, Domingues MA, Fortes AC, Sundermann CV, D'Addio RM, Conrado MS, Rezende SO, Pimentel M da GC. Mining unstructured content for recommender systems: an ensemble approach [Internet]. Information Retrieval Journal. 2016 ; 19( 4): 378-415.[citado 2024 out. 16 ] Available from: https://doi.org/10.1007/s10791-016-9280-8
Trabalho de evento-anais periodico
Improving multivariate data streams clustering (2016)
Bones, Christian Cesar ; Romani, Luciana A. S; Sousa, Elaine Parros Machado de
Source: Procedia Computer Science. Conference titles: International Conference on Computational Science - ICCS. Unidade: ICMC
Subjects: BANCO DE DADOS, MINERAÇÃO DE DADOS, FRACTAIS
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ABNT
BONES, Christian Cesar e ROMANI, Luciana A. S e SOUSA, Elaine Parros Machado de. Improving multivariate data streams clustering. Procedia Computer Science. Amsterdam: Elsevier. Disponível em: https://doi.org/10.1016/j.procs.2016.05.325. Acesso em: 16 out. 2024. , 2016
APA
Bones, C. C., Romani, L. A. S., & Sousa, E. P. M. de. (2016). Improving multivariate data streams clustering. Procedia Computer Science. Amsterdam: Elsevier. doi:10.1016/j.procs.2016.05.325
NLM
Bones CC, Romani LAS, Sousa EPM de. Improving multivariate data streams clustering [Internet]. Procedia Computer Science. 2016 ; 80 461-471.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.procs.2016.05.325
Vancouver
Bones CC, Romani LAS, Sousa EPM de. Improving multivariate data streams clustering [Internet]. Procedia Computer Science. 2016 ; 80 461-471.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.procs.2016.05.325
Artigo de periodico
Simultaneous co-clustering and learning to address the cold start problem in recommender systems (2015)
Pereira, Andre Luiz Vizine; Hruschka, Eduardo Raul
Source: Knowledge-Based Systems. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS
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ABNT
PEREIRA, Andre Luiz Vizine e HRUSCHKA, Eduardo Raul. Simultaneous co-clustering and learning to address the cold start problem in recommender systems. Knowledge-Based Systems, v. 82, p. 11-19, 2015Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2015.02.016. Acesso em: 16 out. 2024.
APA
Pereira, A. L. V., & Hruschka, E. R. (2015). Simultaneous co-clustering and learning to address the cold start problem in recommender systems. Knowledge-Based Systems, 82, 11-19. doi:10.1016/j.knosys.2015.02.016
NLM
Pereira ALV, Hruschka ER. Simultaneous co-clustering and learning to address the cold start problem in recommender systems [Internet]. Knowledge-Based Systems. 2015 ; 82 11-19.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.knosys.2015.02.016
Vancouver
Pereira ALV, Hruschka ER. Simultaneous co-clustering and learning to address the cold start problem in recommender systems [Internet]. Knowledge-Based Systems. 2015 ; 82 11-19.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.knosys.2015.02.016
Artigo de periodico
Interactive textual feature selection for consensus clustering (2015)
Corrêa, Geraldo N; Marcacini, Ricardo Marcondes ; Hruschka, Eduardo Raul ; Rezende, Solange Oliveira
Source: Pattern Recognition Letters. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, MINERAÇÃO DE DADOS
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ABNT
CORRÊA, Geraldo N et al. Interactive textual feature selection for consensus clustering. Pattern Recognition Letters, v. 52, n. ja 2015, p. 25-31, 2015Tradução . . Disponível em: https://doi.org/10.1016/j.patrec.2014.09.008. Acesso em: 16 out. 2024.
APA
Corrêa, G. N., Marcacini, R. M., Hruschka, E. R., & Rezende, S. O. (2015). Interactive textual feature selection for consensus clustering. Pattern Recognition Letters, 52( ja 2015), 25-31. doi:10.1016/j.patrec.2014.09.008
NLM
Corrêa GN, Marcacini RM, Hruschka ER, Rezende SO. Interactive textual feature selection for consensus clustering [Internet]. Pattern Recognition Letters. 2015 ; 52( ja 2015): 25-31.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.patrec.2014.09.008
Vancouver
Corrêa GN, Marcacini RM, Hruschka ER, Rezende SO. Interactive textual feature selection for consensus clustering [Internet]. Pattern Recognition Letters. 2015 ; 52( ja 2015): 25-31.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/j.patrec.2014.09.008
Parte de monografia/livro
Knowledge discovery from data streams (2010)
Gama, João; Rodrigues, Pedro Pereira; Spinosa, Eduardo; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Web intelligence and security : advances in data and text mining techniques for detecting and preventing terrorist activities on the web. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, MINERAÇÃO DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GAMA, João et al. Knowledge discovery from data streams. Web intelligence and security : advances in data and text mining techniques for detecting and preventing terrorist activities on the web. Tradução . Amsterdam: IOS Press, 2010. . Disponível em: https://doi.org/10.3233/978-1-60750-611-9-125. Acesso em: 16 out. 2024.
APA
Gama, J., Rodrigues, P. P., Spinosa, E., & Carvalho, A. C. P. de L. F. de. (2010). Knowledge discovery from data streams. In Web intelligence and security : advances in data and text mining techniques for detecting and preventing terrorist activities on the web. Amsterdam: IOS Press. doi:10.3233/978-1-60750-611-9-125
NLM
Gama J, Rodrigues PP, Spinosa E, Carvalho ACP de LF de. Knowledge discovery from data streams [Internet]. In: Web intelligence and security : advances in data and text mining techniques for detecting and preventing terrorist activities on the web. Amsterdam: IOS Press; 2010. [citado 2024 out. 16 ] Available from: https://doi.org/10.3233/978-1-60750-611-9-125
Vancouver
Gama J, Rodrigues PP, Spinosa E, Carvalho ACP de LF de. Knowledge discovery from data streams [Internet]. In: Web intelligence and security : advances in data and text mining techniques for detecting and preventing terrorist activities on the web. Amsterdam: IOS Press; 2010. [citado 2024 out. 16 ] Available from: https://doi.org/10.3233/978-1-60750-611-9-125
Artigo de periodico
Combining symbolic classifiers from multiple inducers (2003)
Baranauskas, José Augusto; Monard, Maria Carolina
Source: Knowledge-Based Systems. Unidades: FFCLRP, ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, MINERAÇÃO DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BARANAUSKAS, José Augusto e MONARD, Maria Carolina. Combining symbolic classifiers from multiple inducers. Knowledge-Based Systems, v. 16, p. 129-136, 2003Tradução . . Disponível em: https://doi.org/10.1016/s0950-7051(02)00021-7. Acesso em: 16 out. 2024.
APA
Baranauskas, J. A., & Monard, M. C. (2003). Combining symbolic classifiers from multiple inducers. Knowledge-Based Systems, 16, 129-136. doi:10.1016/s0950-7051(02)00021-7
NLM
Baranauskas JA, Monard MC. Combining symbolic classifiers from multiple inducers [Internet]. Knowledge-Based Systems. 2003 ; 16 129-136.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/s0950-7051(02)00021-7
Vancouver
Baranauskas JA, Monard MC. Combining symbolic classifiers from multiple inducers [Internet]. Knowledge-Based Systems. 2003 ; 16 129-136.[citado 2024 out. 16 ] Available from: https://doi.org/10.1016/s0950-7051(02)00021-7

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