Глибокі нейронні мережі для кластеризації масивів даних

Abstract

The rapid advancement of computing technologies has led to an exponential increase in data volumes, creating an urgent need for innovative approaches to data analysis and clustering. Deep neural networks (DNNs) have emerged as powerful tools capable of automatically extracting salient features from raw data, thereby offering promising new directions in clustering applications. This paper reviews the fundamental principles of applying deep neural networks to data clustering, discusses their advantages and limitations compared to traditional methods, and examines practical considerations in their implementation across various domains.