TF*IDF, or term frequency-inverse document frequency, is a numerical statistic used in information retrieval and natural language processing to measure the importance of a term within a document or corpus. It takes into account both the frequency of a term within a document (TF) and the rarity of the term across the entire corpus (IDF). This allows for a more accurate representation of a term’s significance, as it gives higher weight to terms that are both frequent within a document and rare in the overall corpus. TF*IDF is commonly used in search engines, text classification, and document clustering to improve the relevance and accuracy of results.