Di Corso, E.; Proto, S.; Vacchetti, B.; Bethaz, P.; Cerquitelli, T.
Simplifying Text Mining Activities: Scalable and Self-Tuning Methodology for Topic Detection and Characterization. Appl. Sci. 2022, 12, 5125.
https://doi.org/10.3390/app12105125
AMA Style
Di Corso E, Proto S, Vacchetti B, Bethaz P, Cerquitelli T.
Simplifying Text Mining Activities: Scalable and Self-Tuning Methodology for Topic Detection and Characterization. Applied Sciences. 2022; 12(10):5125.
https://doi.org/10.3390/app12105125
Chicago/Turabian Style
Di Corso, Evelina, Stefano Proto, Bartolomeo Vacchetti, Paolo Bethaz, and Tania Cerquitelli.
2022. "Simplifying Text Mining Activities: Scalable and Self-Tuning Methodology for Topic Detection and Characterization" Applied Sciences 12, no. 10: 5125.
https://doi.org/10.3390/app12105125
APA Style
Di Corso, E., Proto, S., Vacchetti, B., Bethaz, P., & Cerquitelli, T.
(2022). Simplifying Text Mining Activities: Scalable and Self-Tuning Methodology for Topic Detection and Characterization. Applied Sciences, 12(10), 5125.
https://doi.org/10.3390/app12105125