Topic Models

Topic modeling is a statistical model used to discover abstract "topics" within a collection of documents. It is a commonly used text mining tool in natural language processing, aiming to reveal the hidden semantic structure in a corpus by analyzing word frequencies and co-occurrence patterns to identify latent topic distributions, thereby achieving efficient organization and understanding of large-scale textual data. Topic models have significant application value in fields such as information retrieval, text classification, and sentiment analysis.