S Zhao, S Zhang, J Liu, H Wang, J Zhu, D Li, R Zhao - Aquaculture, 2021 - Elsevier
Among the background of developments in automation and intelligence, machine learning technology has been extensively applied in aquaculture in recent years, providing a new …
As the COVID-19 pandemic sweeps across the world, it has been accompanied by a tsunami of fake news and misinformation on social media. At the time when reliable …
U Can, B Alatas - Physica A: Statistical Mechanics and its Applications, 2019 - Elsevier
The use of online social networks has made significant progress in recent years as the use of the Internet has become widespread worldwide as the technological infrastructure and the …
Z Guo, L Tang, T Guo, K Yu, M Alazab… - Future generation …, 2021 - Elsevier
Due to the severe threat to cyberspace security, detection of online spammers has been a universal concern of academia. Nowadays, prevailing literature of this field almost leveraged …
Spamming is emerging as a key threat to the Internet of Things (IoT)-based social media applications. It will pose serious security threats to the IoT cyberspace. To this end, artificial …
Nowadays, online spamming has already been a remarkable threat to contents security of Internet of Things. Due to constant technical progress, online spamming activities have been …
WS Chen, Q Zeng, B Pan - Neurocomputing, 2022 - Elsevier
Abstract Deep Nonnegative Matrix Factorization (Deep NMF) is an effective strategy for feature extraction in recent years. By decomposing the matrix recurrently on account of the …
Identity resolution of a person using various online social networks can enable an interested party to have a better and holistic understanding of former's behavior and personality. Major …
A Barushka, P Hajek - Neural Computing and Applications, 2020 - Springer
Spam detection on social networks is increasingly important owing to the rapid growth of social network user base. Sophisticated spam filters must be developed to deal with this …