What is Latent Semantic Analysis?

Latent Semantic Analysis (LSA) is a technique used to analyze and understand relationships between words in large sets of text. It helps identify patterns and semantic meaning by examining how words co-occur in context. LSA is often used in natural language processing (NLP) and information retrieval to improve search engines, content analysis, and machine learning applications.

The main idea behind LSA is that words with similar meanings tend to appear in similar contexts. By reducing the complexity of word relationships into a smaller set of concepts or topics, LSA can uncover hidden connections between terms, even if they don't appear together explicitly. This is useful for improving search relevance, clustering related content, and enhancing content recommendations by identifying the underlying meaning behind words and phrases.