Humor identification in text is essential for natural language understanding, impacting human-computer interactions and emotion recognition. This study introduces a novel approach to automatic humor identification in text using ensemble learning techniques. The objective is to classify text into...

It is essential to innovate and improve service levels by predicting possible process outcomes due to the growth of online service providers. This study estimates the customer satisfaction level based on customer experience analysis. In doing so, we answer recent calls for research about a more...

Urbanization has escalated air pollution levels with subsequent health implications. This study explores the potential of awareness about air quality levels on travelers' choices and proposes machine learning models to predict travel mode under exposure to different air quality levels. These...

This study presents an efficient four-stage ensemble deep learning framework for diagnosing infectious diseases. The model is evaluated on three standard datasets. In our proposed four-stage transfer learning-based deep neural architecture (4s-min-FN), the images pass through four stages, each...