What does tfidf mean? 

Tfidf stands for term frequencyinverse document frequency, and the tfidf weight is a weight often used in information retrieval and text mining. This weight is a statistical measure used to evaluate how important a word is to a document in a collection or corpus. The importance increases proportionally to the number of times a word appears in the document but is offset by the frequency of the word in the corpus. Variations of the tfidf weighting scheme are often used by search engines as a central tool in scoring and ranking a document's relevance given a user query. One of the simplest ranking functions is computed by summing the tfidf for each query term; many more sophisticated ranking functions are variants of this simple model. Tfidf can be successfully used for stopwords filtering in various subject fields including text summarization and classification. To learn more about tfidf or the topics of information retrieval and text mining, we highly recommend Bruce Croft's practical tutorial Search Engines: Information Retrieval in Practice, and the classic Introduction to Information Retrieval by Christ Manning. How to Compute: Typically, the tfidf weight is composed by two terms: the first computes the normalized Term Frequency (TF), aka. the number of times a word appears in a document, divided by the total number of words in that document; the second term is the Inverse Document Frequency (IDF), computed as the logarithm of the number of the documents in the corpus divided by the number of documents where the specific term appears.
See below for a simple example. Example: Consider a document containing 100 words wherein the word cat appears 3 times. The term frequency (i.e., tf) for cat is then (3 / 100) = 0.03. Now, assume we have 10 million documents and the word cat appears in one thousand of these. Then, the inverse document frequency (i.e., idf) is calculated as log(10,000,000 / 1,000) = 4. Thus, the Tfidf weight is the product of these quantities: 0.03 * 4 = 0.12. More Resources:
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