SIGMM: A novel machine learning algorithm for spammer identification in industrial mobile cloud computing
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 …
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 …
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 …
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 …
to construct an effective recommendation engine. In this paper, we present a fused model …
Discovering social spammers from multiple views
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 …
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
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 …
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 …
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
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 …
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 …
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 …
recent years. Modeling traffic helps find strategies for distributing network loads, identifying …