Cite Them Right 11th edition - Harvard

Huynh, V.-N., Honda, K., Le, B., Inuiguchi, M. und Huynh, H.T. (Hrsg.) (2025) Integrated Uncertainty in Knowledge Modelling and Decision Making : 11 th International Symposium, IUKM 2025, Ho Chi Minh City, Vietnam, March 17–19, 2025, Proceedings, Part II [cd]. 1 st ed. 2025, Lecture Notes in Artificial Intelligence. 1 st ed. 2025. Singapore: Springer Nature Singapore. doi:10.1007/978-981-96-4603-6.

Chicago Manual of Style 17th edition (full note)

Huynh, Van-Nam, Katsuhiro Honda, Bac Le, Masahiro Inuiguchi, und Hieu T Huynh, Hrsg. Integrated Uncertainty in Knowledge Modelling and Decision Making : 11 th International Symposium, IUKM 2025, Ho Chi Minh City, Vietnam, March 17–19, 2025, Proceedings, Part II. Cd. Lecture Notes in Artificial Intelligence. 1 st ed. 2025. Singapore: Springer Nature Singapore, [2025?], Singapore: Springer Nature Singapore, [2025?]. https://doi.org/10.1007/978-981-96-4603-6.

American Psychological Association 7th edition

Integrated Uncertainty in Knowledge Modelling and Decision Making : 11 th International Symposium, IUKM 2025, Ho Chi Minh City, Vietnam, March 17–19, 2025, Proceedings, Part II. (ca. 2025). [Cd]. In V.-N. Huynh, K. Honda, B. Le, M. Inuiguchi, & H. T. Huynh (Hrsg.), Lecture Notes in Artificial Intelligence (1 st ed. 2025). Springer Nature Singapore. https://doi.org/10.1007/978-981-96-4603-6

Modern Language Association 9th edition

Huynh, V.-N., K. Honda, B. Le, M. Inuiguchi, und H. T. Huynh, Herausgeber. „Integrated Uncertainty in Knowledge Modelling and Decision Making : 11 th International Symposium, IUKM 2025, Ho Chi Minh City, Vietnam, March 17–19, 2025, Proceedings, Part II“. Lecture Notes in Artificial Intelligence, 1 st ed. 2025, cd, Springer Nature Singapore, 2025, https://doi.org/10.1007/978-981-96-4603-6.

ISO-690 (author-date, Deutsch)

HUYNH, Van-Nam, Katsuhiro HONDA, Bac LE, Masahiro INUIGUCHI und Hieu T HUYNH (Hrsg.). 1 st ed. 2025. Singapore: Springer Nature Singapore. ISBN 9789819646036

Achtung: Diese Zitate sind unter Umständen nicht zu 100% korrekt.