Abstract
The most up-to-date method in text mining is called topic modeling. It is a method for quantitatively figuring out the underlying semantic framework of a collection of documents. About twenty scholarly articles on topic modeling were reviewed to compile the information presented here. Methods for topic modeling, as well as several topic modeling evolution models and their respective applications, are included. Methods for assessing topic modeling, such as Latent Semantic Analysis and Latent Dirichlet Allocation, are also described at length to help readers better grasp the concept of topic modeling. Extensive discussion on subject modeling challenges is included at the end, which will definitely give academics some direction for more fruitful investigation.
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