SIGMM: A novel machine learning algorithm for spammer identification in industrial mobile cloud computing

T Qiu, H Wang, K Li, H Ning… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
An industrial mobile network is crucial for industrial production in the Internet of Things. It
guarantees the normal function of machines and the normalization of industrial production …

Optimizing semantic deep forest for tweet topic classification

KE Daouadi, RZ Rebaï, I Amous - Information Systems, 2021 - Elsevier
Nowadays, topic detection from Twitter attracts the attention of several researchers around
the world. Different topic classification approaches have been proposed as a result of these …

A novel systolic parallel hardware architecture for the FPGA acceleration of feedforward neural networks

LD Medus, T Iakymchuk, JV Frances-Villora… - IEEE …, 2019 - ieeexplore.ieee.org
New chips for machine learning applications appear, they are tuned for a specific topology,
being efficient by using highly parallel designs at the cost of high power or large complex …

A mobile recommendation system based on logistic regression and gradient boosting decision trees

Y Wang, D Feng, D Li, X Chen… - 2016 international joint …, 2016 - ieeexplore.ieee.org
Real-life behaviors shown by the mobile users typically exhibit plenty noises, making it hard
to construct an effective recommendation engine. In this paper, we present a fused model …

Discovering social spammers from multiple views

H Shen, F Ma, X Zhang, L Zong, X Liu, W Liang - Neurocomputing, 2017 - Elsevier
Online social networks have become popular platforms for spammers to spread malicious
content and links. Existing state-of-the-art optimization methods mainly use one kind of user …

A new joint approach with temporal and profile information for social bot detection

Z Yang, X Chen, H Wang, W Wang… - Security and …, 2022 - Wiley Online Library
With the increasing popularity of online social networks (OSNs), a huge number of social
bots have emerged. Social bots are involved in various cybercrimes like cyberbullying and …

[PDF][PDF] Fake accounts detection system based on bidirectional gated recurrent unit neural network

F Benabbou, H Boukhouima, N Sael - International Journal of …, 2022 - academia.edu
Online social networks have become the most widely used medium to interact with friends
and family, share news and important events or publish daily activities. However, this …

LSSL-SSD: Social spammer detection with laplacian score and semi-supervised learning

W Li, M Gao, W Rong, J Wen, Q Xiong… - … Science, Engineering and …, 2016 - Springer
The rapid development of social networks makes it easy for people to communicate online.
However, social networks usually suffer from social spammers due to their openness …

Word embedding for social bot detection systems

Z Ellaky, F Benabbou, S Ouahabi… - 2021 Fifth International …, 2021 - ieeexplore.ieee.org
In recent years, the growth of online social network (OSN) has been very phenomenal with
great social and economic impact. However, some accounts are created for malicious …

[PDF][PDF] Network Traffic Prediction Based on Time Series Modeling

NYA AlSaleem - Iraqi Journal of Science, 2023 - iasj.net
Predicting the network traffic of web pages is one of the areas that has increased focus in
recent years. Modeling traffic helps find strategies for distributing network loads, identifying …