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This lecture introduces Latent Dirichlet Allocation (LDA) as a state-of-the-art method for concept extraction, explaining its probabilistic generative model and the process of document generation using a mixture of topics. It covers topic identification, interpretability of topics, and the use of topic models in unsupervised learning, document retrieval, and document classification.