A feature selection approach for spam detection in social networks using gravitational force-based heuristic algorithm-Reference-Cited by-同舟云学术

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A feature selection approach for spam detection in social networks using gravitational force-based heuristic algorithm

Published:2021-07-16 Issue: Volume: Page:
ISSN:1868-5137
Container-title:Journal of Ambient Intelligence and Humanized Computing
language:en
Short-container-title:J Ambient Intell Human Comput

Author:

Pirozmand Poria,Sadeghilalimi Mehdi,Hosseinabadi Ali Asghar Rahmani,Sadeghilalimi Fatemeh,Mirkamali Seyedsaeid,Slowik Adam

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s12652-021-03385-5.pdf

Reference46 articles.

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2. Bamakan SMH, Wang H, Ravasan AZ (2016a) Parameters optimization for nonparallel support vector machine by particle swarm optimization. Procedia Comput Sci 91:482–491

3. Bamakan SMH, Wang H, Yingjie T, Shi Y (2016b) An effective intrusion detection framework based on MCLP/SVM optimized by time-varying chaos particle swarm optimization. Neurocomputing 199:90–102

4. Barbier G, Liu H (2011) Data mining in social media, social network data analytics. Springer Science Business Media, pp 327–352

5. Bilecen B, Gamper M, Lubbers MJ (2018) The missing link: social network analysis in migration and transnationalism. Soc Netw 53:1–3

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