Latent Semantic Analysis

Latent Semantic Analysis (LSA) is a technique used to analyze relationships between documents and terms by producing a set of concepts related to the documents and terms. It involves constructing a term-document matrix, applying Singular Value Decomposition (SVD) to reduce dimensionality, and then using the reduced space to compare documents and terms. This helps in information retrieval, text categorization, and other natural language processing tasks by capturing underlying semantic relationships.