FL-XGBTC: federated learning inspired with XG-boost tuned classifier for YouTube spam content detection-Reference-Cited by-同舟云学术

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FL-XGBTC: federated learning inspired with XG-boost tuned classifier for YouTube spam content detection

Published:2024-09-14 Issue: Volume: Page:
ISSN:0975-6809
Container-title:International Journal of System Assurance Engineering and Management
language:en
Short-container-title:Int J Syst Assur Eng Manag

Author:

Sharma Vandana,Sinha Anurag^ORCID,Alkhayyat Ahmed,Agarwal Ankit,Nikitha Peddi,Ramkumar Sable,Rathee Tripti,Bhargavi Mopuru,Kumar Nitish

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s13198-024-02502-9.pdf

Reference37 articles.

1. Abdulhamid SM et al (2017) A review on mobile SMS spam filtering techniques. IEEE Access 5:15650–15666. https://doi.org/10.1109/ACCESS.2017.2666785

2. Abu Al-Haija Q, Krichen M, Abu Elhaija W (2022) Machine-learning-based darknet traffic detection system for IoT applications. Electronics 11(4):556. https://doi.org/10.3390/electronics11040556

3. Aiyar S, Shetty NP (2018) N-gram assisted Youtube spam comment detection. Procedia Comput Sci 132:174–182. https://doi.org/10.1016/j.procs.2018.05.181

4. Al-Asadi MA, Tasdemir S (2022) Using artificial intelligence against the phenomenon of fake news: a systematic literature review. In: Lahby M, Pathan A-SK, Maleh Y, Yafooz WMS (eds) Combating fake news with computational intelligence techniques, vol 1001. Springer, Cham, pp 39–54. https://doi.org/10.1007/978-3-030-90087-8_2.

5. Ali A, Amin MZ (2016) An Approach for Spam Detection in YouTube Comments Based on Supervised Learning

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