Sentiment-based predictive models for online purchases in the era of marketing 5.0: a systematic review
The convergence of artificial intelligence (AI), big data (DB), and Internet of Things (IoT) in
Society 5.0, has given rise to Marketing 5.0, revolutionizing personalized customer …
Society 5.0, has given rise to Marketing 5.0, revolutionizing personalized customer …
[HTML][HTML] Bibliometric analysis of the machine learning applications in fraud detection on crowdfunding platforms
Crowdfunding platforms are important for startups, since they offer diverse financing options,
market validation, and promotional opportunities through an investor community. These …
market validation, and promotional opportunities through an investor community. These …
Toward reliable diabetes prediction: Innovations in data engineering and machine learning applications
Objective Diabetes is a metabolic disorder that causes the risk of stroke, heart disease,
kidney failure, and other long-term complications because diabetes generates excess sugar …
kidney failure, and other long-term complications because diabetes generates excess sugar …
Securing transactions: A hybrid dependable ensemble machine learning model using iht-lr and grid search
Financial institutions and businesses face an ongoing challenge from fraudulent
transactions, prompting the need for effective detection methods. Detecting credit card fraud …
transactions, prompting the need for effective detection methods. Detecting credit card fraud …
An integrated multistage ensemble machine learning model for fraudulent transaction detection
Fraudulent transactions continue to pose a concern for financial institutions and
organizations, necessitating the development of effective detection tools. Identification and …
organizations, necessitating the development of effective detection tools. Identification and …
[HTML][HTML] Deep learning-based human activity recognition using CNN, ConvLSTM, and LRCN
Human activity recognition (HAR) plays a crucial role in assisting the elderly and individuals
with vascular dementia by providing support and monitoring for their daily activities. This …
with vascular dementia by providing support and monitoring for their daily activities. This …
MLSTL-WSN: machine learning-based intrusion detection using SMOTETomek in WSNs
In the domain of cyber-physical systems, wireless sensor networks (WSNs) play a pivotal
role as infrastructures, encompassing both stationary and mobile sensors. These sensors …
role as infrastructures, encompassing both stationary and mobile sensors. These sensors …
Enhanced Network Traffic Classification with Machine Learning Algorithms
Network traffic classification plays a critical role in maintaining the security and efficiency of
modern computer networks. Existing techniques often have problems effectively identifying …
modern computer networks. Existing techniques often have problems effectively identifying …
usfAD based effective unknown attack detection focused IDS framework
The rapid expansion of varied network systems, including the Internet of Things (IoT) and the
Industrial Internet of Things (IIoT), has led to an increasing range of cyber threats. Ensuring …
Industrial Internet of Things (IIoT), has led to an increasing range of cyber threats. Ensuring …
[HTML][HTML] A stacked ensemble approach to detect cyber attacks based on feature selection techniques
The exponential growth of data and increased reliance on interconnected systems have
heightened the need for robust network security. Cyber-Attack Detection Systems (CADS) …
heightened the need for robust network security. Cyber-Attack Detection Systems (CADS) …