Exhaustive hyperparameter search techniques such as grid search and random search are widely used in predictive analytics but become computationally expensive and often suboptimal in high-dimensional or nonlinear settings. This challenge is particularly clear in tuning Cycle Reservoir with Jumps...

Social networks are becoming vital for people to interact with each other, which in turn represent the production of a huge amount of information that can be useful in many contexts (e.g., medicine, natural disasters, commercial purposes, tourism). Nevertheless, analyzing such Big Data for...

An adaptive analytics workflow is presented for customer churn prediction, combining Principal Component Analysis for dimensionality reduction, a hybrid Modified Particle Swarm Gravitational Search Optimization (MPSO-GSO) for feature selection and hyperparameter tuning, and an ensemble learning...

Personality prediction has become an increasingly important area in psychological computing and human-centered AI, especially with the rise of user-generated textual data from social media platforms. However, current approaches - primarily based on supervised learning - face major challenges in...

This study aims to identify generative AI (GenAI) applications and develop a roadmap for the near, mid, and far future. Structural topic modeling (STM) is used to discover latent semantic patterns and identify the key application areas from a text corpus comprising 2,398 patents published...