tf–idf

Term Frequency–Inverse Document Frequency (TF-IDF) is a numerical statistic used to reflect the importance of a word in a document relative to a collection of documents. It combines two metrics: Term Frequency (TF), which measures how frequently a term appears in a document, and Inverse Document Frequency (IDF), which assesses the importance of the term by considering how common or rare it is across all documents. TF-IDF is commonly used in information retrieval and text mining to identify and rank the relevance of terms within a document corpus.

tf–idf was discovered on September 11th 2019 and it currently has a search volume of 49.5K with a growth of +3400%.