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| author | Hunter Sezen <ovariegata@yahoo.com> | 2017-12-19 21:43:25 +0000 |
|---|---|---|
| committer | Willy Sudiarto Raharjo <willysr@slackbuilds.org> | 2017-12-21 08:19:23 +0700 |
| commit | 4c4269a4c7d788c7b73f60423aaf01cda72d4f8b (patch) | |
| tree | 25d54b931c01185d920050cefa18c02232ab84f5 /libraries/libexttextcat/README | |
| parent | dec9ed6dfab03059ef9716c95b24e5d995b59a2d (diff) | |
libraries/libexttextcat: Updated for version 3.4.5.
Signed-off-by: David Spencer <idlemoor@slackbuilds.org>
Diffstat (limited to 'libraries/libexttextcat/README')
| -rw-r--r-- | libraries/libexttextcat/README | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/libraries/libexttextcat/README b/libraries/libexttextcat/README index 3b9743c04a4d..9332783b6ed7 100644 --- a/libraries/libexttextcat/README +++ b/libraries/libexttextcat/README @@ -3,7 +3,7 @@ classification technique described in Cavnar & Trenkle, "N-Gram-Based Text Categorization". It was primarily developed for language guessing, a task on which it is known to perform with near-perfect accuracy. - + The central idea of the Cavnar & Trenkle technique is to calculate a "fingerprint" of a document with an unknown category, and compare this with the fingerprints of a number of documents of which the categories @@ -12,7 +12,7 @@ classification. A fingerprint is a list of the most frequent n-grams occurring in a document, ordered by frequency. Fingerprints are compared with a simple out-of-place metric. See the article for more details. - + Considerable effort went into making this implementation fast and efficient. The language guesser processes over 100 documents/second on a simple PC, which makes it practical for many uses. It was developed |