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Artigo de periodico
Latent association rule cluster based model to extract topics for classification and recommendation applications (2018)
Santos, Fabiano Fernandes dos; Domingues, Marcos Aurélio; Sundermann, Camila Vaccari; Carvalho, Veronica Oliveira de; Moura, Maria Fernanda; Rezende, Solange Oliveira
Source: Expert Systems with Applications. Unidade: ICMC
Subjects: MINERAÇÃO DE DADOS, RECONHECIMENTO DE TEXTO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SANTOS, Fabiano Fernandes dos et al. Latent association rule cluster based model to extract topics for classification and recommendation applications. Expert Systems with Applications, v. 112, p. 34-60, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2018.06.021. Acesso em: 25 set. 2024.
APA
Santos, F. F. dos, Domingues, M. A., Sundermann, C. V., Carvalho, V. O. de, Moura, M. F., & Rezende, S. O. (2018). Latent association rule cluster based model to extract topics for classification and recommendation applications. Expert Systems with Applications, 112, 34-60. doi:10.1016/j.eswa.2018.06.021
NLM
Santos FF dos, Domingues MA, Sundermann CV, Carvalho VO de, Moura MF, Rezende SO. Latent association rule cluster based model to extract topics for classification and recommendation applications [Internet]. Expert Systems with Applications. 2018 ; 112 34-60.[citado 2024 set. 25 ] Available from: https://doi.org/10.1016/j.eswa.2018.06.021
Vancouver
Santos FF dos, Domingues MA, Sundermann CV, Carvalho VO de, Moura MF, Rezende SO. Latent association rule cluster based model to extract topics for classification and recommendation applications [Internet]. Expert Systems with Applications. 2018 ; 112 34-60.[citado 2024 set. 25 ] Available from: https://doi.org/10.1016/j.eswa.2018.06.021
Artigo de periodico
Cross-domain aspect extraction for sentiment analysis: a transductive learning approach (2018)
Marcacini, Ricardo Marcondes ; Rossi, Rafael Geraldeli; Matsuno, Ivone Penque; Rezende, Solange Oliveira
Source: Decision Support Systems. Unidade: ICMC
Subjects: MINERAÇÃO DE DADOS, RECONHECIMENTO DE TEXTO, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARCACINI, Ricardo Marcondes et al. Cross-domain aspect extraction for sentiment analysis: a transductive learning approach. Decision Support Systems, v. 114, p. 70-80, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.dss.2018.08.009. Acesso em: 25 set. 2024.
APA
Marcacini, R. M., Rossi, R. G., Matsuno, I. P., & Rezende, S. O. (2018). Cross-domain aspect extraction for sentiment analysis: a transductive learning approach. Decision Support Systems, 114, 70-80. doi:10.1016/j.dss.2018.08.009
NLM
Marcacini RM, Rossi RG, Matsuno IP, Rezende SO. Cross-domain aspect extraction for sentiment analysis: a transductive learning approach [Internet]. Decision Support Systems. 2018 ; 114 70-80.[citado 2024 set. 25 ] Available from: https://doi.org/10.1016/j.dss.2018.08.009
Vancouver
Marcacini RM, Rossi RG, Matsuno IP, Rezende SO. Cross-domain aspect extraction for sentiment analysis: a transductive learning approach [Internet]. Decision Support Systems. 2018 ; 114 70-80.[citado 2024 set. 25 ] Available from: https://doi.org/10.1016/j.dss.2018.08.009
Artigo de periodico
Using bipartite heterogeneous networks to speed up inductive semi-supervised learning and improve automatic text categorization (2017)
Rossi, Rafael Geraldeli; Lopes, Alneu de Andrade ; Rezende, Solange Oliveira
Source: Knowledge-Based Systems. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE TEXTO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ROSSI, Rafael Geraldeli e LOPES, Alneu de Andrade e REZENDE, Solange Oliveira. Using bipartite heterogeneous networks to speed up inductive semi-supervised learning and improve automatic text categorization. Knowledge-Based Systems, v. 132, p. Se 2017, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2017.06.016. Acesso em: 25 set. 2024.
APA
Rossi, R. G., Lopes, A. de A., & Rezende, S. O. (2017). Using bipartite heterogeneous networks to speed up inductive semi-supervised learning and improve automatic text categorization. Knowledge-Based Systems, 132, Se 2017. doi:10.1016/j.knosys.2017.06.016
NLM
Rossi RG, Lopes A de A, Rezende SO. Using bipartite heterogeneous networks to speed up inductive semi-supervised learning and improve automatic text categorization [Internet]. Knowledge-Based Systems. 2017 ; 132 Se 2017.[citado 2024 set. 25 ] Available from: https://doi.org/10.1016/j.knosys.2017.06.016
Vancouver
Rossi RG, Lopes A de A, Rezende SO. Using bipartite heterogeneous networks to speed up inductive semi-supervised learning and improve automatic text categorization [Internet]. Knowledge-Based Systems. 2017 ; 132 Se 2017.[citado 2024 set. 25 ] Available from: https://doi.org/10.1016/j.knosys.2017.06.016
Artigo de periodico
Optimization and label propagation in bipartite heterogeneous networks to improve transductive classification of texts (2016)
Rossi, Rafael Geraldeli; Lopes, Alneu de Andrade ; Rezende, Solange Oliveira
Source: Information Processing and Management. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, MINERAÇÃO DE DADOS, RECONHECIMENTO DE TEXTO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ROSSI, Rafael Geraldeli e LOPES, Alneu de Andrade e REZENDE, Solange Oliveira. Optimization and label propagation in bipartite heterogeneous networks to improve transductive classification of texts. Information Processing and Management, v. 52, n. 2, p. 217-257, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.ipm.2015.07.004. Acesso em: 25 set. 2024.
APA
Rossi, R. G., Lopes, A. de A., & Rezende, S. O. (2016). Optimization and label propagation in bipartite heterogeneous networks to improve transductive classification of texts. Information Processing and Management, 52( 2), 217-257. doi:10.1016/j.ipm.2015.07.004
NLM
Rossi RG, Lopes A de A, Rezende SO. Optimization and label propagation in bipartite heterogeneous networks to improve transductive classification of texts [Internet]. Information Processing and Management. 2016 ; 52( 2): 217-257.[citado 2024 set. 25 ] Available from: https://doi.org/10.1016/j.ipm.2015.07.004
Vancouver
Rossi RG, Lopes A de A, Rezende SO. Optimization and label propagation in bipartite heterogeneous networks to improve transductive classification of texts [Internet]. Information Processing and Management. 2016 ; 52( 2): 217-257.[citado 2024 set. 25 ] Available from: https://doi.org/10.1016/j.ipm.2015.07.004
Artigo de periodico
Privileged contextual information for context-aware recommender systems (2016)
Sundermann, Camila Vaccari; Domingues, Marcos Aurélio; Conrado, Merley da Silva; Rezende, Solange Oliveira
Source: Expert Systems with Applications. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SUNDERMANN, Camila Vaccari et al. Privileged contextual information for context-aware recommender systems. Expert Systems with Applications, v. 57, p. Se 2016, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2016.03.036. Acesso em: 25 set. 2024.
APA
Sundermann, C. V., Domingues, M. A., Conrado, M. da S., & Rezende, S. O. (2016). Privileged contextual information for context-aware recommender systems. Expert Systems with Applications, 57, Se 2016. doi:10.1016/j.eswa.2016.03.036
NLM
Sundermann CV, Domingues MA, Conrado M da S, Rezende SO. Privileged contextual information for context-aware recommender systems [Internet]. Expert Systems with Applications. 2016 ; 57 Se 2016.[citado 2024 set. 25 ] Available from: https://doi.org/10.1016/j.eswa.2016.03.036
Vancouver
Sundermann CV, Domingues MA, Conrado M da S, Rezende SO. Privileged contextual information for context-aware recommender systems [Internet]. Expert Systems with Applications. 2016 ; 57 Se 2016.[citado 2024 set. 25 ] Available from: https://doi.org/10.1016/j.eswa.2016.03.036
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 25 set. 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 set. 25 ] 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 set. 25 ] Available from: https://doi.org/10.1016/j.patrec.2014.09.008

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