Difference between revisions of "Log Tempered TF-IDF"
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| − | Log Tempered TF-IDF is a variant of the standard information retrieval TF-IDF metric. This metric gives a a weight to how important a word is to a document in a given corpus | + | Log Tempered TF-IDF is a variant [[category::method]] of calculating the standard [[AddressesProblem::Information Retrieval|information retrieval]] TF-IDF metric. This metric gives a a weight to how important a word is to a document in a given corpus, and is often used in search engines as part of the scoring / ranking of a document's relevance to a query. |
== Algorithm / Calculation == | == Algorithm / Calculation == | ||
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[[File:lt-tfidf.png]] | [[File:lt-tfidf.png]] | ||
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| + | == Relevant Papers == | ||
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| + | {{#ask: [[UsesMethod::Log Tempered TF-IDF]] | ||
| + | | ?AddressesProblem | ||
| + | | ?UsesDataset | ||
| + | }} | ||
Latest revision as of 02:26, 31 March 2011
Log Tempered TF-IDF is a variant method of calculating the standard information retrieval TF-IDF metric. This metric gives a a weight to how important a word is to a document in a given corpus, and is often used in search engines as part of the scoring / ranking of a document's relevance to a query.
Algorithm / Calculation
Given a document and a corpus, we first calculate the following:
- Term Frequency:
- A measure of importance of a given term to a document. Frequency of a term for a given document.
- Inverse Document Frequency:
- A measure of general importance of a term in a corpus
Then the log tempered tf-idf for a word is given by the following:
