TF-IDF (term frequency-inverse document frequency) is a way of
determining which terms in a document should be weighted most
heavily when trying to understand what the document is about.
The term frequency reflects how often a given term appears in
the document of interest. The document frequency is measured
with respect to a corpus of other documents. It tells you how
often the term appears in your corpus overall. The terms that
are most informative about a particular text have a high term
frequency and a low document frequency. The TF-IDF for a term is
the product of its term frequency and the scaled inverse of its
document frequency. Stopwords are those words that occur so
frequently in the language that they rarely convey information
about the meaning of a particular document. In this
Demonstration, stopwords can be turned on and off, and the font
size of each term can be scaled by various weighting factors.