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Artigo de periodico
Boosting collaborative filtering with an ensemble of co-trained recommenders (2019)
Costa, Arthur F. da; Manzato, Marcelo Garcia ; Campello, Ricardo José Gabrielli Barreto
Source: Expert Systems with Applications. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, SISTEMAS DE INFORMAÇÃO, RECONHECIMENTO DE PADRÕES
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ABNT
COSTA, Arthur F. da e MANZATO, Marcelo Garcia e CAMPELLO, Ricardo José Gabrielli Barreto. Boosting collaborative filtering with an ensemble of co-trained recommenders. Expert Systems with Applications, v. 115, n. Ja 2019, p. 427-441, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2018.08.020. Acesso em: 01 nov. 2024.
APA
Costa, A. F. da, Manzato, M. G., & Campello, R. J. G. B. (2019). Boosting collaborative filtering with an ensemble of co-trained recommenders. Expert Systems with Applications, 115( Ja 2019), 427-441. doi:10.1016/j.eswa.2018.08.020
NLM
Costa AF da, Manzato MG, Campello RJGB. Boosting collaborative filtering with an ensemble of co-trained recommenders [Internet]. Expert Systems with Applications. 2019 ; 115( Ja 2019): 427-441.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.eswa.2018.08.020
Vancouver
Costa AF da, Manzato MG, Campello RJGB. Boosting collaborative filtering with an ensemble of co-trained recommenders [Internet]. Expert Systems with Applications. 2019 ; 115( Ja 2019): 427-441.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.eswa.2018.08.020
Artigo de periodico
Combining semantic and term frequency similarities for text clustering (2019)
Soares, Victor Hugo Andrade ; Campello, Ricardo José Gabrielli Barreto ; Nourashrafeddin, Seyednaser ; Milios, Evangelos ; Naldi, Murilo Coelho
Source: Knowledge and Information Systems. Unidade: ICMC
Subjects: MINERAÇÃO DE DADOS, RECONHECIMENTO DE TEXTO, DESCOBERTA DE CONHECIMENTO
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SOARES, Victor Hugo Andrade et al. Combining semantic and term frequency similarities for text clustering. Knowledge and Information Systems, v. 61, n. 3, p. 1485-1516, 2019Tradução . . Disponível em: https://doi.org/10.1007/s10115-018-1278-7. Acesso em: 01 nov. 2024.
APA
Soares, V. H. A., Campello, R. J. G. B., Nourashrafeddin, S., Milios, E., & Naldi, M. C. (2019). Combining semantic and term frequency similarities for text clustering. Knowledge and Information Systems, 61( 3), 1485-1516. doi:10.1007/s10115-018-1278-7
NLM
Soares VHA, Campello RJGB, Nourashrafeddin S, Milios E, Naldi MC. Combining semantic and term frequency similarities for text clustering [Internet]. Knowledge and Information Systems. 2019 ; 61( 3): 1485-1516.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1007/s10115-018-1278-7
Vancouver
Soares VHA, Campello RJGB, Nourashrafeddin S, Milios E, Naldi MC. Combining semantic and term frequency similarities for text clustering [Internet]. Knowledge and Information Systems. 2019 ; 61( 3): 1485-1516.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1007/s10115-018-1278-7
Trabalho de evento-resumo
Case recommender: a flexible and extensible Python framework for recommender systems (2018)
Costa, Arthur da; Fressato, Eduardo; Neto, Fernando; Manzato, Marcelo Garcia ; Campello, Ricardo José Gabrielli Barreto
Source: Proceedings. Conference titles: ACM Conference on Recommender Systems - RecSys. Unidade: ICMC
Subjects: SISTEMAS DE INFORMAÇÃO, RECONHECIMENTO DE PADRÕES, PYTHON
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ABNT
COSTA, Arthur da et al. Case recommender: a flexible and extensible Python framework for recommender systems. 2018, Anais.. New York: ACM, 2018. Disponível em: https://doi.org/10.1145/3240323.3241611. Acesso em: 01 nov. 2024.
APA
Costa, A. da, Fressato, E., Neto, F., Manzato, M. G., & Campello, R. J. G. B. (2018). Case recommender: a flexible and extensible Python framework for recommender systems. In Proceedings. New York: ACM. doi:10.1145/3240323.3241611
NLM
Costa A da, Fressato E, Neto F, Manzato MG, Campello RJGB. Case recommender: a flexible and extensible Python framework for recommender systems [Internet]. Proceedings. 2018 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/3240323.3241611
Vancouver
Costa A da, Fressato E, Neto F, Manzato MG, Campello RJGB. Case recommender: a flexible and extensible Python framework for recommender systems [Internet]. Proceedings. 2018 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/3240323.3241611
Trabalho de evento
A unified framework of density-based clustering for semi-supervised classification (2018)
Gertrudes, Jadson Castro; Zimek, Arthur; Sander, Jörg; Campello, Ricardo José Gabrielli Barreto
Source: Proceedings. Conference titles: International Conference on Scientific and Statistical Database Management - SSDBM. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, ALGORITMOS ÚTEIS E ESPECÍFICOS
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ABNT
GERTRUDES, Jadson Castro et al. A unified framework of density-based clustering for semi-supervised classification. 2018, Anais.. New York: ACM, 2018. Disponível em: https://doi.org/10.1145/3221269.3223037. Acesso em: 01 nov. 2024.
APA
Gertrudes, J. C., Zimek, A., Sander, J., & Campello, R. J. G. B. (2018). A unified framework of density-based clustering for semi-supervised classification. In Proceedings. New York: ACM. doi:10.1145/3221269.3223037
NLM
Gertrudes JC, Zimek A, Sander J, Campello RJGB. A unified framework of density-based clustering for semi-supervised classification [Internet]. Proceedings. 2018 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/3221269.3223037
Vancouver
Gertrudes JC, Zimek A, Sander J, Campello RJGB. A unified framework of density-based clustering for semi-supervised classification [Internet]. Proceedings. 2018 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/3221269.3223037
Artigo de periodico
Clustering of RNA-Seq samples: comparison study on cancer data (2018)
Jaskowiak, Pablo Andretta; Costa, Ivan G; Campello, Ricardo José Gabrielli Barreto
Source: Methods. Unidade: ICMC
Subjects: BIOINFORMÁTICA, RECONHECIMENTO DE PADRÕES, EXPRESSÃO GÊNICA, NEOPLASIAS
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ABNT
JASKOWIAK, Pablo Andretta e COSTA, Ivan G e CAMPELLO, Ricardo José Gabrielli Barreto. Clustering of RNA-Seq samples: comparison study on cancer data. Methods, v. 132, n. Ja 2018, p. 42-49, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.ymeth.2017.07.023. Acesso em: 01 nov. 2024.
APA
Jaskowiak, P. A., Costa, I. G., & Campello, R. J. G. B. (2018). Clustering of RNA-Seq samples: comparison study on cancer data. Methods, 132( Ja 2018), 42-49. doi:10.1016/j.ymeth.2017.07.023
NLM
Jaskowiak PA, Costa IG, Campello RJGB. Clustering of RNA-Seq samples: comparison study on cancer data [Internet]. Methods. 2018 ; 132( Ja 2018): 42-49.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.ymeth.2017.07.023
Vancouver
Jaskowiak PA, Costa IG, Campello RJGB. Clustering of RNA-Seq samples: comparison study on cancer data [Internet]. Methods. 2018 ; 132( Ja 2018): 42-49.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.ymeth.2017.07.023
Trabalho de evento
CoRec: a co-training approach for recommender systems (2018)
Costa, Arthur F. da; Manzato, Marcelo Garcia ; Campello, Ricardo José Gabrielli Barreto
Source: Proceedings. Conference titles: Symposium on Applied Computing - SAC. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, SISTEMAS DE INFORMAÇÃO, RECONHECIMENTO DE PADRÕES
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ABNT
COSTA, Arthur F. da e MANZATO, Marcelo Garcia e CAMPELLO, Ricardo José Gabrielli Barreto. CoRec: a co-training approach for recommender systems. 2018, Anais.. New York: ACM, 2018. Disponível em: https://doi.org/10.1145/3167132.3167209. Acesso em: 01 nov. 2024.
APA
Costa, A. F. da, Manzato, M. G., & Campello, R. J. G. B. (2018). CoRec: a co-training approach for recommender systems. In Proceedings. New York: ACM. doi:10.1145/3167132.3167209
NLM
Costa AF da, Manzato MG, Campello RJGB. CoRec: a co-training approach for recommender systems [Internet]. Proceedings. 2018 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/3167132.3167209
Vancouver
Costa AF da, Manzato MG, Campello RJGB. CoRec: a co-training approach for recommender systems [Internet]. Proceedings. 2018 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/3167132.3167209
Artigo de periodico
Ensemble clustering approaches applied in group-based collaborative filtering supported by multiple users' feedback (2017)
Costa, Arthur F. da; Manzato, Marcelo Garcia ; Campello, Ricardo José Gabrielli Barreto
Source: Journal of Information and Data Management - JIDM. Unidade: ICMC
Subjects: RECONHECIMENTO DE PADRÕES, RECUPERAÇÃO DA INFORMAÇÃO
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ABNT
COSTA, Arthur F. da e MANZATO, Marcelo Garcia e CAMPELLO, Ricardo José Gabrielli Barreto. Ensemble clustering approaches applied in group-based collaborative filtering supported by multiple users' feedback. Journal of Information and Data Management - JIDM, v. 8, n. 3, p. 180-196, 2017Tradução . . Disponível em: https://seer.ufmg.br/index.php/jidm/article/view/4560. Acesso em: 01 nov. 2024.
APA
Costa, A. F. da, Manzato, M. G., & Campello, R. J. G. B. (2017). Ensemble clustering approaches applied in group-based collaborative filtering supported by multiple users' feedback. Journal of Information and Data Management - JIDM, 8( 3), 180-196. Recuperado de https://seer.ufmg.br/index.php/jidm/article/view/4560
NLM
Costa AF da, Manzato MG, Campello RJGB. Ensemble clustering approaches applied in group-based collaborative filtering supported by multiple users' feedback [Internet]. Journal of Information and Data Management - JIDM. 2017 ; 8( 3): 180-196.[citado 2024 nov. 01 ] Available from: https://seer.ufmg.br/index.php/jidm/article/view/4560
Vancouver
Costa AF da, Manzato MG, Campello RJGB. Ensemble clustering approaches applied in group-based collaborative filtering supported by multiple users' feedback [Internet]. Journal of Information and Data Management - JIDM. 2017 ; 8( 3): 180-196.[citado 2024 nov. 01 ] Available from: https://seer.ufmg.br/index.php/jidm/article/view/4560
Artigo de periodico
A systematic comparative evaluation of biclustering techniques (2017)
Padilha, Victor A; Campello, Ricardo José Gabrielli Barreto
Source: BMC Bioinformatics. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, RECONHECIMENTO DE PADRÕES, BIOINFORMÁTICA, EXPRESSÃO GÊNICA
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ABNT
PADILHA, Victor A e CAMPELLO, Ricardo José Gabrielli Barreto. A systematic comparative evaluation of biclustering techniques. BMC Bioinformatics, v. 18, p. 1-25, 2017Tradução . . Disponível em: https://doi.org/10.1186/s12859-017-1487-1. Acesso em: 01 nov. 2024.
APA
Padilha, V. A., & Campello, R. J. G. B. (2017). A systematic comparative evaluation of biclustering techniques. BMC Bioinformatics, 18, 1-25. doi:10.1186/s12859-017-1487-1
NLM
Padilha VA, Campello RJGB. A systematic comparative evaluation of biclustering techniques [Internet]. BMC Bioinformatics. 2017 ; 18 1-25.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1186/s12859-017-1487-1
Vancouver
Padilha VA, Campello RJGB. A systematic comparative evaluation of biclustering techniques [Internet]. BMC Bioinformatics. 2017 ; 18 1-25.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1186/s12859-017-1487-1
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: 01 nov. 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 nov. 01 ] 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 nov. 01 ] Available from: https://doi.org/10.1016/j.neucom.2016.07.074
Trabalho de evento
Efficient computation of multiple density-based clustering hierarchies (2017)
Araujo Neto, Antonio Cavalcante; Sander, Joerg; Campello, Ricardo José Gabrielli Barreto; Nascimento, Mario A
Source: Proceedings. Conference titles: IEEE International Conference on Data Mining - ICDM. Unidade: ICMC
Subjects: RECONHECIMENTO DE PADRÕES, MINERAÇÃO DE DADOS, DESCOBERTA DE CONHECIMENTO
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ABNT
ARAUJO NETO, Antonio Cavalcante et al. Efficient computation of multiple density-based clustering hierarchies. 2017, Anais.. Piscataway: IEEE, 2017. Disponível em: https://doi.org/10.1109/ICDM.2017.127. Acesso em: 01 nov. 2024.
APA
Araujo Neto, A. C., Sander, J., Campello, R. J. G. B., & Nascimento, M. A. (2017). Efficient computation of multiple density-based clustering hierarchies. In Proceedings. Piscataway: IEEE. doi:10.1109/ICDM.2017.127
NLM
Araujo Neto AC, Sander J, Campello RJGB, Nascimento MA. Efficient computation of multiple density-based clustering hierarchies [Internet]. Proceedings. 2017 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/ICDM.2017.127
Vancouver
Araujo Neto AC, Sander J, Campello RJGB, Nascimento MA. Efficient computation of multiple density-based clustering hierarchies [Internet]. Proceedings. 2017 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/ICDM.2017.127
Parte de monografia/livro
Relative validity criteria for community mining algorithms (2017)
Rabbany, Reihaneh; Takaffoli, Mansoreh; Fagnan, Justin; Zaïane, Osmar R; Campello, Ricardo José Gabrielli Barreto
Source: Encyclopedia of social network analysis and mining. Unidade: ICMC
Subjects: MINERAÇÃO DE DADOS, DESCOBERTA DE CONHECIMENTO
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ABNT
RABBANY, Reihaneh et al. Relative validity criteria for community mining algorithms. Encyclopedia of social network analysis and mining. Tradução . New York: Springer, 2017. . Disponível em: https://doi.org/10.1007/978-1-4614-7163-9_356-1. Acesso em: 01 nov. 2024.
APA
Rabbany, R., Takaffoli, M., Fagnan, J., Zaïane, O. R., & Campello, R. J. G. B. (2017). Relative validity criteria for community mining algorithms. In Encyclopedia of social network analysis and mining. New York: Springer. doi:10.1007/978-1-4614-7163-9_356-1
NLM
Rabbany R, Takaffoli M, Fagnan J, Zaïane OR, Campello RJGB. Relative validity criteria for community mining algorithms [Internet]. In: Encyclopedia of social network analysis and mining. New York: Springer; 2017. [citado 2024 nov. 01 ] Available from: https://doi.org/10.1007/978-1-4614-7163-9_356-1
Vancouver
Rabbany R, Takaffoli M, Fagnan J, Zaïane OR, Campello RJGB. Relative validity criteria for community mining algorithms [Internet]. In: Encyclopedia of social network analysis and mining. New York: Springer; 2017. [citado 2024 nov. 01 ] Available from: https://doi.org/10.1007/978-1-4614-7163-9_356-1
Artigo de periodico
On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study (2016)
Campos, Guilherme O; Zimek, Arthur; Sander, Jörg; Campello, Ricardo José Gabrielli Barreto; Micenková, Barbora; Schubert, Erich; Assent, Ira; Houle, Michael E
Source: Data Mining and Knowledge Discovery. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
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ABNT
CAMPOS, Guilherme O et al. On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study. Data Mining and Knowledge Discovery, v. 30, n. 4, p. 891-927, 2016Tradução . . Disponível em: https://doi.org/10.1007/s10618-015-0444-8. Acesso em: 01 nov. 2024.
APA
Campos, G. O., Zimek, A., Sander, J., Campello, R. J. G. B., Micenková, B., Schubert, E., et al. (2016). On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study. Data Mining and Knowledge Discovery, 30( 4), 891-927. doi:10.1007/s10618-015-0444-8
NLM
Campos GO, Zimek A, Sander J, Campello RJGB, Micenková B, Schubert E, Assent I, Houle ME. On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study [Internet]. Data Mining and Knowledge Discovery. 2016 ; 30( 4): 891-927.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1007/s10618-015-0444-8
Vancouver
Campos GO, Zimek A, Sander J, Campello RJGB, Micenková B, Schubert E, Assent I, Houle ME. On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study [Internet]. Data Mining and Knowledge Discovery. 2016 ; 30( 4): 891-927.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1007/s10618-015-0444-8
Trabalho de evento
On the evaluation of outlier detection and one-class classification methods (2016)
Swersky, Lorne; Marques, Henrique O; Sander, Jörg; Campello, Ricardo José Gabrielli Barreto; Zimek, Arthur
Source: Proceedings. Conference titles: IEEE International Conference on Data Science and Advanced Analytics - DSAA. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES
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ABNT
SWERSKY, Lorne et al. On the evaluation of outlier detection and one-class classification methods. 2016, Anais.. Los Alamitos: IEEE, 2016. Disponível em: https://doi.org/10.1109/DSAA.2016.8. Acesso em: 01 nov. 2024.
APA
Swersky, L., Marques, H. O., Sander, J., Campello, R. J. G. B., & Zimek, A. (2016). On the evaluation of outlier detection and one-class classification methods. In Proceedings. Los Alamitos: IEEE. doi:10.1109/DSAA.2016.8
NLM
Swersky L, Marques HO, Sander J, Campello RJGB, Zimek A. On the evaluation of outlier detection and one-class classification methods [Internet]. Proceedings. 2016 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/DSAA.2016.8
Vancouver
Swersky L, Marques HO, Sander J, Campello RJGB, Zimek A. On the evaluation of outlier detection and one-class classification methods [Internet]. Proceedings. 2016 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/DSAA.2016.8
Trabalho de evento
Exploiting different users' interactions for profiles enrichment in recommender systems (2016)
Costa, Arthur F. da; Martins, Rafael D; Manzato, Marcelo Garcia ; Campello, Ricardo José Gabrielli Barreto
Source: Proceedings. Conference titles: Symposium on Applied Computing - SAC. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, SISTEMAS DE INFORMAÇÃO, WORLD WIDE WEB
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ABNT
COSTA, Arthur F. da et al. Exploiting different users' interactions for profiles enrichment in recommender systems. 2016, Anais.. New York: ACM, 2016. Disponível em: https://doi.org/10.1145/2851613.2851923. Acesso em: 01 nov. 2024.
APA
Costa, A. F. da, Martins, R. D., Manzato, M. G., & Campello, R. J. G. B. (2016). Exploiting different users' interactions for profiles enrichment in recommender systems. In Proceedings. New York: ACM. doi:10.1145/2851613.2851923
NLM
Costa AF da, Martins RD, Manzato MG, Campello RJGB. Exploiting different users' interactions for profiles enrichment in recommender systems [Internet]. Proceedings. 2016 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/2851613.2851923
Vancouver
Costa AF da, Martins RD, Manzato MG, Campello RJGB. Exploiting different users' interactions for profiles enrichment in recommender systems [Internet]. Proceedings. 2016 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/2851613.2851923
Trabalho de evento
Active semi-supervised classification based on multiple clustering hierarchies (2016)
Batista, Antônio J. L; Campello, Ricardo José Gabrielli Barreto; Sander, Jörg
Source: Proceedings. Conference titles: IEEE International Conference on Data Science and Advanced Analytics - DSAA. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES
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ABNT
BATISTA, Antônio J. L e CAMPELLO, Ricardo José Gabrielli Barreto e SANDER, Jörg. Active semi-supervised classification based on multiple clustering hierarchies. 2016, Anais.. Los Alamitos: IEEE, 2016. Disponível em: https://doi.org/10.1109/DSAA.2016.9. Acesso em: 01 nov. 2024.
APA
Batista, A. J. L., Campello, R. J. G. B., & Sander, J. (2016). Active semi-supervised classification based on multiple clustering hierarchies. In Proceedings. Los Alamitos: IEEE. doi:10.1109/DSAA.2016.9
NLM
Batista AJL, Campello RJGB, Sander J. Active semi-supervised classification based on multiple clustering hierarchies [Internet]. Proceedings. 2016 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/DSAA.2016.9
Vancouver
Batista AJL, Campello RJGB, Sander J. Active semi-supervised classification based on multiple clustering hierarchies [Internet]. Proceedings. 2016 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/DSAA.2016.9
Artigo de periodico
On strategies for building effective ensembles of relative clustering validity criteria (2016)
Jaskowiak, Pablo A; Moulavi, Davoud; Furtado, Antonio C. S; Campello, Ricardo José Gabrielli Barreto; Zimek, Arthur; Sander, Jörg
Source: Knowledge and Information Systems. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
JASKOWIAK, Pablo A et al. On strategies for building effective ensembles of relative clustering validity criteria. Knowledge and Information Systems, v. 47, n. 2, p. 329-354, 2016Tradução . . Disponível em: https://doi.org/10.1007/s10115-015-0851-6. Acesso em: 01 nov. 2024.
APA
Jaskowiak, P. A., Moulavi, D., Furtado, A. C. S., Campello, R. J. G. B., Zimek, A., & Sander, J. (2016). On strategies for building effective ensembles of relative clustering validity criteria. Knowledge and Information Systems, 47( 2), 329-354. doi:10.1007/s10115-015-0851-6
NLM
Jaskowiak PA, Moulavi D, Furtado ACS, Campello RJGB, Zimek A, Sander J. On strategies for building effective ensembles of relative clustering validity criteria [Internet]. Knowledge and Information Systems. 2016 ; 47( 2): 329-354.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1007/s10115-015-0851-6
Vancouver
Jaskowiak PA, Moulavi D, Furtado ACS, Campello RJGB, Zimek A, Sander J. On strategies for building effective ensembles of relative clustering validity criteria [Internet]. Knowledge and Information Systems. 2016 ; 47( 2): 329-354.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1007/s10115-015-0851-6
Trabalho de evento
Group-based collaborative filtering supported by multiple users' feedback to improve personalized ranking (2016)
Costa, Arthur F. da; Manzato, Marcelo Garcia ; Campello, Ricardo José Gabrielli Barreto
Source: Proceedings. Conference titles: Brazilian Symposium on Multimedia and the Web - WebMedia. Unidade: ICMC
Subjects: MULTIMÍDIA INTERATIVA, SISTEMAS DE INFORMAÇÃO, RECONHECIMENTO DE PADRÕES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COSTA, Arthur F. da e MANZATO, Marcelo Garcia e CAMPELLO, Ricardo José Gabrielli Barreto. Group-based collaborative filtering supported by multiple users' feedback to improve personalized ranking. 2016, Anais.. New York: ACM, 2016. Disponível em: https://doi.org/10.1145/2976796.2976852. Acesso em: 01 nov. 2024.
APA
Costa, A. F. da, Manzato, M. G., & Campello, R. J. G. B. (2016). Group-based collaborative filtering supported by multiple users' feedback to improve personalized ranking. In Proceedings. New York: ACM. doi:10.1145/2976796.2976852
NLM
Costa AF da, Manzato MG, Campello RJGB. Group-based collaborative filtering supported by multiple users' feedback to improve personalized ranking [Internet]. Proceedings. 2016 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/2976796.2976852
Vancouver
Costa AF da, Manzato MG, Campello RJGB. Group-based collaborative filtering supported by multiple users' feedback to improve personalized ranking [Internet]. Proceedings. 2016 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/2976796.2976852
Artigo de periodico
Hierarchical density estimates for data clustering, visualization, and outlier detection (2015)
Campello, Ricardo José Gabrielli Barreto; Moulavi, Davoud; Zimek, Arthur; Sander, Jörg
Source: ACM Transactions on Knowledge Discovery from Data. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, MINERAÇÃO DE DADOS, RECUPERAÇÃO DA INFORMAÇÃO, RECONHECIMENTO DE PADRÕES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAMPELLO, Ricardo José Gabrielli Barreto et al. Hierarchical density estimates for data clustering, visualization, and outlier detection. ACM Transactions on Knowledge Discovery from Data, v. 10, n. 1, p. 5:1-5:51, 2015Tradução . . Disponível em: https://doi.org/10.1145/2733381. Acesso em: 01 nov. 2024.
APA
Campello, R. J. G. B., Moulavi, D., Zimek, A., & Sander, J. (2015). Hierarchical density estimates for data clustering, visualization, and outlier detection. ACM Transactions on Knowledge Discovery from Data, 10( 1), 5:1-5:51. doi:10.1145/2733381
NLM
Campello RJGB, Moulavi D, Zimek A, Sander J. Hierarchical density estimates for data clustering, visualization, and outlier detection [Internet]. ACM Transactions on Knowledge Discovery from Data. 2015 ; 10( 1): 5:1-5:51.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/2733381
Vancouver
Campello RJGB, Moulavi D, Zimek A, Sander J. Hierarchical density estimates for data clustering, visualization, and outlier detection [Internet]. ACM Transactions on Knowledge Discovery from Data. 2015 ; 10( 1): 5:1-5:51.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1145/2733381
Artigo de periodico
Comparing hard and overlapping clusterings (2015)
Horta, Danilo; Campello, Ricardo José Gabrielli Barreto
Source: Journal of Machine Learning Research. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HORTA, Danilo e CAMPELLO, Ricardo José Gabrielli Barreto. Comparing hard and overlapping clusterings. Journal of Machine Learning Research, v. 16, p. 2949-2997, 2015Tradução . . Disponível em: http://jmlr.org/papers/volume16/horta15a/horta15a.pdf. Acesso em: 01 nov. 2024.
APA
Horta, D., & Campello, R. J. G. B. (2015). Comparing hard and overlapping clusterings. Journal of Machine Learning Research, 16, 2949-2997. Recuperado de http://jmlr.org/papers/volume16/horta15a/horta15a.pdf
NLM
Horta D, Campello RJGB. Comparing hard and overlapping clusterings [Internet]. Journal of Machine Learning Research. 2015 ; 16 2949-2997.[citado 2024 nov. 01 ] Available from: http://jmlr.org/papers/volume16/horta15a/horta15a.pdf
Vancouver
Horta D, Campello RJGB. Comparing hard and overlapping clusterings [Internet]. Journal of Machine Learning Research. 2015 ; 16 2949-2997.[citado 2024 nov. 01 ] Available from: http://jmlr.org/papers/volume16/horta15a/horta15a.pdf
Artigo de periodico
Comparison of distributed evolutionary k-means clustering algorithms (2015)
Naldi, M. C; Campello, Ricardo José Gabrielli Barreto
Source: Neurocomputing. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NALDI, M. C e CAMPELLO, Ricardo José Gabrielli Barreto. Comparison of distributed evolutionary k-means clustering algorithms. Neurocomputing, v. 163, p. 78-93, 2015Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2014.07.083. Acesso em: 01 nov. 2024.
APA
Naldi, M. C., & Campello, R. J. G. B. (2015). Comparison of distributed evolutionary k-means clustering algorithms. Neurocomputing, 163, 78-93. doi:10.1016/j.neucom.2014.07.083
NLM
Naldi MC, Campello RJGB. Comparison of distributed evolutionary k-means clustering algorithms [Internet]. Neurocomputing. 2015 ; 163 78-93.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.neucom.2014.07.083
Vancouver
Naldi MC, Campello RJGB. Comparison of distributed evolutionary k-means clustering algorithms [Internet]. Neurocomputing. 2015 ; 163 78-93.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.neucom.2014.07.083

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