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: The standard process includes corpus collection, preprocessing (e.g., creating a document-term-matrix), model estimation, and validation.

Topic modeling has become a cornerstone of natural language processing (NLP), enabling researchers to summarize and navigate massive document archives. This paper explores the transition from traditional probabilistic models to modern neural architectures. 071408apeamelbrnldn pdf

: Integration of deep neural networks has led to Neural Topic Models (NTMs) , which facilitate complex tasks like text generation and summarization. creating a document-term-matrix)

: Advanced models now capture the evolution of topics over time or within hierarchical document structures. 3. Methodologies and Evaluation 071408apeamelbrnldn pdf

1. Introduction