Latent Semantic Analysis (LSA) is a powerful mathematical model that uncovers the underlying structure of language, offering insights into semantic relationships. It reduces the dimensionality of a term-document matrix using Singular Value Decomposition (SVD) to identify concepts, making it valuable for information retrieval, document classification, and cognitive science. LSA’s significance persists amidst advancements in deep learning and NLP.