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  • Source: Knowledge-Based Systems. Unidade: ICMC

    Subjects: RECONHECIMENTO DE TEXTO, FRAMEWORKS, PLATAFORMA DIGITAL, CORRUPÇÃO DE MENORES

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      MILON-FLORES, Daniela Fernanda e CORDEIRO, Robson Leonardo Ferreira. How to take advantage of behavioral features for the early detection of grooming in online conversations. Knowledge-Based Systems, v. 240, p. 1-29, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2021.108017. Acesso em: 05 dez. 2025.
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      Milon-Flores, D. F., & Cordeiro, R. L. F. (2022). How to take advantage of behavioral features for the early detection of grooming in online conversations. Knowledge-Based Systems, 240, 1-29. doi:10.1016/j.knosys.2021.108017
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      Milon-Flores DF, Cordeiro RLF. How to take advantage of behavioral features for the early detection of grooming in online conversations [Internet]. Knowledge-Based Systems. 2022 ; 240 1-29.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2021.108017
    • Vancouver

      Milon-Flores DF, Cordeiro RLF. How to take advantage of behavioral features for the early detection of grooming in online conversations [Internet]. Knowledge-Based Systems. 2022 ; 240 1-29.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2021.108017
  • Source: Knowledge-Based Systems. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, ALGORITMOS E ESTRUTURAS DE DADOS

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      RIVOLLI, Adriano et al. Meta-features for meta-learning. Knowledge-Based Systems, v. 240, p. 1-21, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2021.108101. Acesso em: 05 dez. 2025.
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      Rivolli, A., Garcia, L. P. F., Soares, C., Vanschoren, J., & Carvalho, A. C. P. de L. F. de. (2022). Meta-features for meta-learning. Knowledge-Based Systems, 240, 1-21. doi:10.1016/j.knosys.2021.108101
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      Rivolli A, Garcia LPF, Soares C, Vanschoren J, Carvalho ACP de LF de. Meta-features for meta-learning [Internet]. Knowledge-Based Systems. 2022 ; 240 1-21.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2021.108101
    • Vancouver

      Rivolli A, Garcia LPF, Soares C, Vanschoren J, Carvalho ACP de LF de. Meta-features for meta-learning [Internet]. Knowledge-Based Systems. 2022 ; 240 1-21.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2021.108101
  • Source: Knowledge-Based Systems. Unidades: ICMC, FMRP, Interinstitucional de Pós-Graduação em Estatística

    Subjects: COVID-19, EQUIPAMENTO DE PROTEÇÃO INDIVIDUAL, MODELOS PARA PROCESSOS ESTOCÁSTICOS

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      GONZATTO JUNIOR, Oilson Alberto et al. Safety-Stock: predicting the demand for supplies in Brazilian hospitals during the COVID-19 pandemic. Knowledge-Based Systems, v. 247, p. 1-10, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2022.108753. Acesso em: 05 dez. 2025.
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      Gonzatto Junior, O. A., Nascimento, D. C. do, Russo, C. M., Henriques, M. J., Tomazella, C. P., Santos, M. O. dos, et al. (2022). Safety-Stock: predicting the demand for supplies in Brazilian hospitals during the COVID-19 pandemic. Knowledge-Based Systems, 247, 1-10. doi:10.1016/j.knosys.2022.108753
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      Gonzatto Junior OA, Nascimento DC do, Russo CM, Henriques MJ, Tomazella CP, Santos MO dos, Neves D, Assad D, Guerra R, Bertazo EK, Cuminato JA, Louzada F. Safety-Stock: predicting the demand for supplies in Brazilian hospitals during the COVID-19 pandemic [Internet]. Knowledge-Based Systems. 2022 ; 247 1-10.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2022.108753
    • Vancouver

      Gonzatto Junior OA, Nascimento DC do, Russo CM, Henriques MJ, Tomazella CP, Santos MO dos, Neves D, Assad D, Guerra R, Bertazo EK, Cuminato JA, Louzada F. Safety-Stock: predicting the demand for supplies in Brazilian hospitals during the COVID-19 pandemic [Internet]. Knowledge-Based Systems. 2022 ; 247 1-10.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2022.108753
  • Source: Knowledge-Based Systems. Unidade: ICMC

    Subjects: RECONHECIMENTO DE TEXTO, ALGORITMOS ÚTEIS E ESPECÍFICOS, WEB SEMÂNTICA

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      ZANON, André Levi e ROCHA, Leonardo Chaves Dutra da e MANZATO, Marcelo Garcia. Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data. Knowledge-Based Systems, v. 252, p. Se 2022, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2022.109333. Acesso em: 05 dez. 2025.
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      Zanon, A. L., Rocha, L. C. D. da, & Manzato, M. G. (2022). Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data. Knowledge-Based Systems, 252, Se 2022. doi:10.1016/j.knosys.2022.109333
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      Zanon AL, Rocha LCD da, Manzato MG. Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data [Internet]. Knowledge-Based Systems. 2022 ; 252 Se 2022.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2022.109333
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      Zanon AL, Rocha LCD da, Manzato MG. Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data [Internet]. Knowledge-Based Systems. 2022 ; 252 Se 2022.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2022.109333
  • Source: Knowledge-Based Systems. Unidade: ICMC

    Subjects: PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), COMPUTAÇÃO RECONFIGURÁVEL, TRÁFEGO RODOVIÁRIO

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      ALVES, Matheus Aparecido do Carmo e CORDEIRO, Robson Leonardo Ferreira. Effective and unburdensome forecast of highway traffic flow with adaptive computing. Knowledge-Based Systems, v. 212, n. Ja 2021, p. 1-13, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2020.106603. Acesso em: 05 dez. 2025.
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      Alves, M. A. do C., & Cordeiro, R. L. F. (2021). Effective and unburdensome forecast of highway traffic flow with adaptive computing. Knowledge-Based Systems, 212( Ja 2021), 1-13. doi:10.1016/j.knosys.2020.106603
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      Alves MA do C, Cordeiro RLF. Effective and unburdensome forecast of highway traffic flow with adaptive computing [Internet]. Knowledge-Based Systems. 2021 ; 212( Ja 2021): 1-13.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2020.106603
    • Vancouver

      Alves MA do C, Cordeiro RLF. Effective and unburdensome forecast of highway traffic flow with adaptive computing [Internet]. Knowledge-Based Systems. 2021 ; 212( Ja 2021): 1-13.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2020.106603
  • Source: Knowledge-Based Systems. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, ALGORITMOS ÚTEIS E ESPECÍFICOS

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      PIMENTEL, Bruno Almeida e CARVALHO, André Carlos Ponce de Leon Ferreira de. A meta-learning approach for recommending the number of clusters for clustering algorithms. Knowledge-Based Systems, v. 195, p. 1-14, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2020.105682. Acesso em: 05 dez. 2025.
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      Pimentel, B. A., & Carvalho, A. C. P. de L. F. de. (2020). A meta-learning approach for recommending the number of clusters for clustering algorithms. Knowledge-Based Systems, 195, 1-14. doi:10.1016/j.knosys.2020.105682
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      Pimentel BA, Carvalho ACP de LF de. A meta-learning approach for recommending the number of clusters for clustering algorithms [Internet]. Knowledge-Based Systems. 2020 ; 195 1-14.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2020.105682
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      Pimentel BA, Carvalho ACP de LF de. A meta-learning approach for recommending the number of clusters for clustering algorithms [Internet]. Knowledge-Based Systems. 2020 ; 195 1-14.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2020.105682
  • Source: Knowledge-Based Systems. Unidade: ICMC

    Subjects: REDES COMPLEXAS, VISUALIZAÇÃO

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      VALEJO, Alan Demetrius Baria et al. A coarsening method for bipartite networks via weight-constrained label propagation. Knowledge-Based Systems, v. 195, p. 1-17, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2020.105678. Acesso em: 05 dez. 2025.
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      Valejo, A. D. B., Faleiros, T., Oliveira, M. C. F. de, & Lopes, A. de A. (2020). A coarsening method for bipartite networks via weight-constrained label propagation. Knowledge-Based Systems, 195, 1-17. doi:10.1016/j.knosys.2020.105678
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      Valejo ADB, Faleiros T, Oliveira MCF de, Lopes A de A. A coarsening method for bipartite networks via weight-constrained label propagation [Internet]. Knowledge-Based Systems. 2020 ; 195 1-17.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2020.105678
    • Vancouver

      Valejo ADB, Faleiros T, Oliveira MCF de, Lopes A de A. A coarsening method for bipartite networks via weight-constrained label propagation [Internet]. Knowledge-Based Systems. 2020 ; 195 1-17.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2020.105678
  • Source: Knowledge-Based Systems. Unidade: ICMC

    Subjects: BANCO DE DADOS, MINERAÇÃO DE DADOS, FRACTAIS

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      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: 05 dez. 2025.
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      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
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      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 2025 dez. 05 ] 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 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2020.105777
  • Source: Knowledge-Based Systems. Unidade: ICMC

    Subjects: BANCO DE DADOS, RECUPERAÇÃO DA INFORMAÇÃO, RECONHECIMENTO DE TEXTO

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      TEKLI, Joe et al. SemIndex+: a semantic indexing scheme for structured, unstructured, and partly structured data. Knowledge-Based Systems, v. 164, n. Ja 2019, p. 378-403, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2018.11.010. Acesso em: 05 dez. 2025.
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      Tekli, J., Chbeir, R., Traina, A. J. M., & Traina Junior, C. (2019). SemIndex+: a semantic indexing scheme for structured, unstructured, and partly structured data. Knowledge-Based Systems, 164( Ja 2019), 378-403. doi:10.1016/j.knosys.2018.11.010
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      Tekli J, Chbeir R, Traina AJM, Traina Junior C. SemIndex+: a semantic indexing scheme for structured, unstructured, and partly structured data [Internet]. Knowledge-Based Systems. 2019 ; 164( Ja 2019): 378-403.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2018.11.010
    • Vancouver

      Tekli J, Chbeir R, Traina AJM, Traina Junior C. SemIndex+: a semantic indexing scheme for structured, unstructured, and partly structured data [Internet]. Knowledge-Based Systems. 2019 ; 164( Ja 2019): 378-403.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2018.11.010
  • Source: Knowledge-Based Systems. Unidade: ICMC

    Subjects: MINERAÇÃO DE DADOS, RECONHECIMENTO DE TEXTO

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      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: 05 dez. 2025.
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      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
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      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 2025 dez. 05 ] 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 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2018.10.026
  • Source: Knowledge-Based Systems. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE DADOS, RECONHECIMENTO DE PADRÕES

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      GARCIA, Luís P. F et al. New label noise injection methods for the evaluation of noise filters. Knowledge-Based Systems, v. 163, n. Ja 2019, p. 693-704, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2018.09.031. Acesso em: 05 dez. 2025.
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      Garcia, L. P. F., Lehmann, J., Carvalho, A. C. P. de L. F. de, & Lorena, A. C. (2019). New label noise injection methods for the evaluation of noise filters. Knowledge-Based Systems, 163( Ja 2019), 693-704. doi:10.1016/j.knosys.2018.09.031
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      Garcia LPF, Lehmann J, Carvalho ACP de LF de, Lorena AC. New label noise injection methods for the evaluation of noise filters [Internet]. Knowledge-Based Systems. 2019 ; 163( Ja 2019): 693-704.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2018.09.031
    • Vancouver

      Garcia LPF, Lehmann J, Carvalho ACP de LF de, Lorena AC. New label noise injection methods for the evaluation of noise filters [Internet]. Knowledge-Based Systems. 2019 ; 163( Ja 2019): 693-704.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2018.09.031
  • Source: Knowledge-Based Systems. Unidade: EESC

    Assunto: ENGENHARIA ELÉTRICA

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      GROSS, Tadeu Junior et al. An analytical threshold for combining Bayesian Networks. Knowledge-Based Systems, v. 175, p. 36-49, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2019.03.014. Acesso em: 05 dez. 2025.
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      Gross, T. J., Bessani, M., Darwin Junior, W., Araújo, R. B., Vale, F. de A. C. do, & Maciel, C. D. (2019). An analytical threshold for combining Bayesian Networks. Knowledge-Based Systems, 175, 36-49. doi:10.1016/j.knosys.2019.03.014
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      Gross TJ, Bessani M, Darwin Junior W, Araújo RB, Vale F de AC do, Maciel CD. An analytical threshold for combining Bayesian Networks [Internet]. Knowledge-Based Systems. 2019 ; 175 36-49.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2019.03.014
    • Vancouver

      Gross TJ, Bessani M, Darwin Junior W, Araújo RB, Vale F de AC do, Maciel CD. An analytical threshold for combining Bayesian Networks [Internet]. Knowledge-Based Systems. 2019 ; 175 36-49.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2019.03.014
  • Source: Knowledge-Based Systems. Unidade: ICMC

    Subjects: REDES COMPLEXAS, OTIMIZAÇÃO COMBINATÓRIA, HEURÍSTICA

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      VALEJO, Alan et al. Multilevel approach for combinatorial optimization in bipartite network. Knowledge-Based Systems, v. 151, p. 45-61, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2018.03.021. Acesso em: 05 dez. 2025.
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      Valejo, A., Oliveira, M. C. F. de, Rocha Filho, G. P., & Lopes, A. de A. (2018). Multilevel approach for combinatorial optimization in bipartite network. Knowledge-Based Systems, 151, 45-61. doi:10.1016/j.knosys.2018.03.021
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      Valejo A, Oliveira MCF de, Rocha Filho GP, Lopes A de A. Multilevel approach for combinatorial optimization in bipartite network [Internet]. Knowledge-Based Systems. 2018 ; 151 45-61.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2018.03.021
    • Vancouver

      Valejo A, Oliveira MCF de, Rocha Filho GP, Lopes A de A. Multilevel approach for combinatorial optimization in bipartite network [Internet]. Knowledge-Based Systems. 2018 ; 151 45-61.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2018.03.021
  • Source: Knowledge-Based Systems. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE TEXTO

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      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: 05 dez. 2025.
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      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
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      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 2025 dez. 05 ] 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 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2017.06.016
  • Source: Knowledge-Based Systems. Unidade: FFCLRP

    Assunto: BIOINFORMÁTICA

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      PEREZ, Pedro Santoro et al. Windowing improvements towards more comprehensible models. Knowledge-Based Systems, v. 92, p. 9-22, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2015.10.011. Acesso em: 05 dez. 2025.
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      Perez, P. S., Nozawa, S. R., Macedo, A. A., & Baranauskas, J. A. (2016). Windowing improvements towards more comprehensible models. Knowledge-Based Systems, 92, 9-22. doi:10.1016/j.knosys.2015.10.011
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      Perez PS, Nozawa SR, Macedo AA, Baranauskas JA. Windowing improvements towards more comprehensible models [Internet]. Knowledge-Based Systems. 2016 ; 92 9-22.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2015.10.011
    • Vancouver

      Perez PS, Nozawa SR, Macedo AA, Baranauskas JA. Windowing improvements towards more comprehensible models [Internet]. Knowledge-Based Systems. 2016 ; 92 9-22.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/j.knosys.2015.10.011
  • Source: Knowledge-Based Systems. Unidade: IME

    Subjects: SISTEMAS BASEADOS EM CONHECIMENTO, REPRESENTAÇÃO DE CONHECIMENTO

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      SILVA, Flávio Soares Corrêa da et al. On the insufficiency of ontologies: problems in knowledge sharing and alternative solutions. Knowledge-Based Systems, v. 15, n. 3, p. 147-167, 2002Tradução . . Disponível em: https://doi.org/10.1016/s0950-7051(01)00152-6. Acesso em: 05 dez. 2025.
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      Silva, F. S. C. da, Vasconcelos, W. W. M. P. de, Robertson, D. S., Brilhante, V., Melo, A. C. V. de, Finger, M., & Agustí, J. (2002). On the insufficiency of ontologies: problems in knowledge sharing and alternative solutions. Knowledge-Based Systems, 15( 3), 147-167. doi:10.1016/s0950-7051(01)00152-6
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      Silva FSC da, Vasconcelos WWMP de, Robertson DS, Brilhante V, Melo ACV de, Finger M, Agustí J. On the insufficiency of ontologies: problems in knowledge sharing and alternative solutions [Internet]. Knowledge-Based Systems. 2002 ; 15( 3): 147-167.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/s0950-7051(01)00152-6
    • Vancouver

      Silva FSC da, Vasconcelos WWMP de, Robertson DS, Brilhante V, Melo ACV de, Finger M, Agustí J. On the insufficiency of ontologies: problems in knowledge sharing and alternative solutions [Internet]. Knowledge-Based Systems. 2002 ; 15( 3): 147-167.[citado 2025 dez. 05 ] Available from: https://doi.org/10.1016/s0950-7051(01)00152-6

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