A time series can often be characterized using machine learning techniques, which require feature vectors as input. The quality of the feature vectors reflects the accuracy of the utilized machine learning techniques. We propose a method for combining features extracted from two popular...

Investigating the correlations between graph metrics in various networks is a prosperous research topic that only starts to evolve. Knowledge about graph metrics interrelations may be beneficial in many other aspects of networks studying, starting from optimizing computations to even detecting...

ChatGPT has demonstrated remarkable capabilities across various natural language processing (NLP) tasks. However, its potential for inferring dynamic network structures from temporal textual data, specifically financial news, remains an unexplored frontier. In this research, we introduce a novel...