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Topic Modeling - Types, Working, Applications - GeeksforGeeks Topic modelling is a powerful text mining approach that allows researchers, businesses, and selection-makers to discover the hidden thematic structures within big collections of unstructured textual content facts Its importance may be summarized as follows:
Topic Models vs. Unstructured Data - Communications of the ACM Topic models use Bayesian statistics and machine learning to discover the thematic content of unlabeled documents, provide application-specific roadmaps through them, and predict the nature of future documents in a collection
Topic Modeling: Algorithms, Techniques, and Application Algorithms and Techniques used in Improving Topic Modeling Some algorithms used for Topic Modeling tasks are Latent Dirichlet Allocation, Latent Semantic Analysis, Correlated Topic Modeling, and Probabilistic Latent Semantic Analysis Here are some specifications on the algorithms