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Filtros : "Financiamento AFRL" "Financiamento FCT" Removido: "1951" Limpar

Filtros

Trabalho de evento
TGRAPP: anomaly detection and visualization of large-scale call graphs (2023)
Cazzolato, Mirela Teixeira ; Vijayakumar, Saranya; Zheng, Xinyi; Park, Namyong; Lee, Meng-Chieh; Chau, Duen Horng ; Fidalgo, Pedro; Lages, Bruno; Traina, Agma Juci Machado ; Faloutsos, Christos
Source: Proceedings. Conference titles: AAAI Conference on Artificial Intelligence - AAAI. Unidade: ICMC
Subjects: RECUPERAÇÃO DA INFORMAÇÃO, VISUALIZAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela Teixeira et al. TGRAPP: anomaly detection and visualization of large-scale call graphs. 2023, Anais.. Washington: AAAI Press, 2023. Disponível em: https://doi.org/10.1609/aaai.v37i13.27062. Acesso em: 06 nov. 2024.
APA
Cazzolato, M. T., Vijayakumar, S., Zheng, X., Park, N., Lee, M. -C., Chau, D. H., et al. (2023). TGRAPP: anomaly detection and visualization of large-scale call graphs. In Proceedings. Washington: AAAI Press. doi:10.1609/aaai.v37i13.27062
NLM
Cazzolato MT, Vijayakumar S, Zheng X, Park N, Lee M-C, Chau DH, Fidalgo P, Lages B, Traina AJM, Faloutsos C. TGRAPP: anomaly detection and visualization of large-scale call graphs [Internet]. Proceedings. 2023 ;[citado 2024 nov. 06 ] Available from: https://doi.org/10.1609/aaai.v37i13.27062
Vancouver
Cazzolato MT, Vijayakumar S, Zheng X, Park N, Lee M-C, Chau DH, Fidalgo P, Lages B, Traina AJM, Faloutsos C. TGRAPP: anomaly detection and visualization of large-scale call graphs [Internet]. Proceedings. 2023 ;[citado 2024 nov. 06 ] Available from: https://doi.org/10.1609/aaai.v37i13.27062
Trabalho de evento
TgraphSpot: fast and effective anomaly detection for time-evolving graphs (2022)
Cazzolato, Mirela Teixeira ; Vijayakumar, Saranya; Zheng, Xinyi; Park, Namyong; Lee, Meng-Chieh; Fidalgo, Pedro; Lages, Bruno; Traina, Agma Juci Machado ; Faloutsos, Christos
Source: Proceedings. Conference titles: IEEE International Conference on Big Data - Big Data. Unidade: ICMC
Subjects: RECUPERAÇÃO DA INFORMAÇÃO, VISUALIZAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela Teixeira et al. TgraphSpot: fast and effective anomaly detection for time-evolving graphs. 2022, Anais.. Piscataway: IEEE, 2022. Disponível em: https://doi.org/10.1109/BigData55660.2022.10020898. Acesso em: 06 nov. 2024.
APA
Cazzolato, M. T., Vijayakumar, S., Zheng, X., Park, N., Lee, M. -C., Fidalgo, P., et al. (2022). TgraphSpot: fast and effective anomaly detection for time-evolving graphs. In Proceedings. Piscataway: IEEE. doi:10.1109/BigData55660.2022.10020898
NLM
Cazzolato MT, Vijayakumar S, Zheng X, Park N, Lee M-C, Fidalgo P, Lages B, Traina AJM, Faloutsos C. TgraphSpot: fast and effective anomaly detection for time-evolving graphs [Internet]. Proceedings. 2022 ;[citado 2024 nov. 06 ] Available from: https://doi.org/10.1109/BigData55660.2022.10020898
Vancouver
Cazzolato MT, Vijayakumar S, Zheng X, Park N, Lee M-C, Fidalgo P, Lages B, Traina AJM, Faloutsos C. TgraphSpot: fast and effective anomaly detection for time-evolving graphs [Internet]. Proceedings. 2022 ;[citado 2024 nov. 06 ] Available from: https://doi.org/10.1109/BigData55660.2022.10020898

Digital Library of Intellectual Production of Universidade de São Paulo 2012 - 2024