Valery Solovyev – Honored Professor, Kazan Federal University, Institute of Philology and Intercultural Communication, Republic of Tatarstan, Russia

Series: Computer Science, Technology and Applications
BISAC: COM042000; COM018000
DOI: https://doi.org/10.52305/NADQ0452

Topic Modeling: Techniques, Applications, and Emerging Trends in Text Analysis contains four chapters that aim to introduce readers to state-of-the-art methods and demonstrate their successful application in complex scenarios. Chapter 1 provides a mathematically rigorous yet hopefully accessible survey of Neural topic models, written for researchers and practitioners who want to understand not just what these models do but why they are designed the way they are. Chapter 2 provides a survey of the current state of research in probabilistic topic modeling (PTM) within the framework of additive regularization for topic modeling (ARTM). Chapter 3 presents a comprehensive analysis of automatic topic labeling, focusing on three major trends: internal source methods, external source methods, and approaches requiring Large Language Models (LLMs). Finally, chapter 4 investigates the problem of conducting topic modeling on a particularly refractory corpus: Russian-language reviews of museums.

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