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Artigo de periodico
Integrated detection and localization of concept drifts in process mining with batch and stream trace clustering support (2023)
Sousa, Rafael Gaspar de ; Meira Neto, Antonio Carlos ; Fantinato, Marcelo ; Peres, Sarajane Marques ; Reijers, Hajo Alexander
Source: Data & Knowledge Engineering. Unidade: EACH
Assunto: MINERAÇÃO DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUSA, Rafael Gaspar de et al. Integrated detection and localization of concept drifts in process mining with batch and stream trace clustering support. Data & Knowledge Engineering, p. 01-51, 2023Tradução . . Disponível em: http://dx.doi.org/10.1016/j.datak.2023.102253. Acesso em: 16 maio 2024.
APA
Sousa, R. G. de, Meira Neto, A. C., Fantinato, M., Peres, S. M., & Reijers, H. A. (2023). Integrated detection and localization of concept drifts in process mining with batch and stream trace clustering support. Data & Knowledge Engineering, 01-51. doi:10.1016/j.datak.2023.102253
NLM
Sousa RG de, Meira Neto AC, Fantinato M, Peres SM, Reijers HA. Integrated detection and localization of concept drifts in process mining with batch and stream trace clustering support [Internet]. Data & Knowledge Engineering. 2023 ; 01-51.[citado 2024 maio 16 ] Available from: http://dx.doi.org/10.1016/j.datak.2023.102253
Vancouver
Sousa RG de, Meira Neto AC, Fantinato M, Peres SM, Reijers HA. Integrated detection and localization of concept drifts in process mining with batch and stream trace clustering support [Internet]. Data & Knowledge Engineering. 2023 ; 01-51.[citado 2024 maio 16 ] Available from: http://dx.doi.org/10.1016/j.datak.2023.102253
Artigo de periodico
X-Processes: process model discovery with the best balance among fitness, precision, simplicity, and generalization through a genetic algorithm (2023)
Fantinato, Marcelo ; Peres, Sarajane Marques ; Reijers, Hajo Alexander
Source: Information Systems: databases: their creation, management and utilization. Unidade: EACH
Assunto: GENERALIZAÇÃO (APRENDIZAGEM)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FANTINATO, Marcelo e PERES, Sarajane Marques e REIJERS, Hajo Alexander. X-Processes: process model discovery with the best balance among fitness, precision, simplicity, and generalization through a genetic algorithm. Information Systems: databases: their creation, management and utilization, v. 119, p. 01-25, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.is.2023.102247. Acesso em: 16 maio 2024.
APA
Fantinato, M., Peres, S. M., & Reijers, H. A. (2023). X-Processes: process model discovery with the best balance among fitness, precision, simplicity, and generalization through a genetic algorithm. Information Systems: databases: their creation, management and utilization, 119, 01-25. doi:10.1016/j.is.2023.102247
NLM
Fantinato M, Peres SM, Reijers HA. X-Processes: process model discovery with the best balance among fitness, precision, simplicity, and generalization through a genetic algorithm [Internet]. Information Systems: databases: their creation, management and utilization. 2023 ; 119 01-25.[citado 2024 maio 16 ] Available from: https://doi.org/10.1016/j.is.2023.102247
Vancouver
Fantinato M, Peres SM, Reijers HA. X-Processes: process model discovery with the best balance among fitness, precision, simplicity, and generalization through a genetic algorithm [Internet]. Information Systems: databases: their creation, management and utilization. 2023 ; 119 01-25.[citado 2024 maio 16 ] Available from: https://doi.org/10.1016/j.is.2023.102247
Dissertação (Mestrado)
Trace clustering approach for detection and locatization of concept drift in business processes (2021)
Sousa, Rafael Gaspar de; Peres, Sarajane Marques (Orientador) ; Reijers, Hajo Alexander (Orientador)
Unidade: EACH
Subjects: MINERAÇÃO DE DADOS, NEGÓCIOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUSA, Rafael Gaspar de. Trace clustering approach for detection and locatization of concept drift in business processes. 2021. Dissertação (Mestrado) – Universidade de São Paulo, São Paulo, 2021. Disponível em: https://www.teses.usp.br/teses/disponiveis/100/100131/tde-02122021-144602/. Acesso em: 16 maio 2024.
APA
Sousa, R. G. de. (2021). Trace clustering approach for detection and locatization of concept drift in business processes (Dissertação (Mestrado). Universidade de São Paulo, São Paulo. Recuperado de https://www.teses.usp.br/teses/disponiveis/100/100131/tde-02122021-144602/
NLM
Sousa RG de. Trace clustering approach for detection and locatization of concept drift in business processes [Internet]. 2021 ;[citado 2024 maio 16 ] Available from: https://www.teses.usp.br/teses/disponiveis/100/100131/tde-02122021-144602/
Vancouver
Sousa RG de. Trace clustering approach for detection and locatization of concept drift in business processes [Internet]. 2021 ;[citado 2024 maio 16 ] Available from: https://www.teses.usp.br/teses/disponiveis/100/100131/tde-02122021-144602/
Trabalho de evento
Concept drift detection and localization in process mining: an integrated and efficient approach enabled by trace clustering (2021)
Sousa, Rafael Gaspar de; Peres, Sarajane Marques ; Fantinato, Marcelo ; Reijers, Hajo Alexander
Source: Proceedings. Conference titles: Annual ACM Symposium on Applied Computing. Unidade: EACH
Subjects: MINERAÇÃO DE DADOS, NEGÓCIOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUSA, Rafael Gaspar de et al. Concept drift detection and localization in process mining: an integrated and efficient approach enabled by trace clustering. 2021, Anais.. New York: ACM, 2021. Disponível em: https://doi.org/10.1145/3412841.3441918. Acesso em: 16 maio 2024.
APA
Sousa, R. G. de, Peres, S. M., Fantinato, M., & Reijers, H. A. (2021). Concept drift detection and localization in process mining: an integrated and efficient approach enabled by trace clustering. In Proceedings. New York: ACM. doi:10.1145/3412841.3441918
NLM
Sousa RG de, Peres SM, Fantinato M, Reijers HA. Concept drift detection and localization in process mining: an integrated and efficient approach enabled by trace clustering [Internet]. Proceedings. 2021 ;[citado 2024 maio 16 ] Available from: https://doi.org/10.1145/3412841.3441918
Vancouver
Sousa RG de, Peres SM, Fantinato M, Reijers HA. Concept drift detection and localization in process mining: an integrated and efficient approach enabled by trace clustering [Internet]. Proceedings. 2021 ;[citado 2024 maio 16 ] Available from: https://doi.org/10.1145/3412841.3441918
Artigo de periodico
Interactive clustering: a scoping review (2020)
Neubauer, Thais Rodrigues ; Peres, Sarajane Marques ; Fantinato, Marcelo ; Lu, Xixi; Reijers, Hajo Alexander
Source: Artificial Intelligence Review. Unidade: EACH
Subjects: MINERAÇÃO DE DADOS, NEGÓCIOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NEUBAUER, Thais Rodrigues et al. Interactive clustering: a scoping review. Artificial Intelligence Review, p. 01-62, 2020Tradução . . Disponível em: https://doi.org/10.1007/s10462-020-09913-7. Acesso em: 16 maio 2024.
APA
Neubauer, T. R., Peres, S. M., Fantinato, M., Lu, X., & Reijers, H. A. (2020). Interactive clustering: a scoping review. Artificial Intelligence Review, 01-62. doi:10.1007/s10462-020-09913-7
NLM
Neubauer TR, Peres SM, Fantinato M, Lu X, Reijers HA. Interactive clustering: a scoping review [Internet]. Artificial Intelligence Review. 2020 ; 01-62.[citado 2024 maio 16 ] Available from: https://doi.org/10.1007/s10462-020-09913-7
Vancouver
Neubauer TR, Peres SM, Fantinato M, Lu X, Reijers HA. Interactive clustering: a scoping review [Internet]. Artificial Intelligence Review. 2020 ; 01-62.[citado 2024 maio 16 ] Available from: https://doi.org/10.1007/s10462-020-09913-7

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