Difference between revisions of "Automatic key extraction"

Revision as of 16:17, 20 September 2010

OpenKM uses KEA for extracting keyphrases from text documents. KEA it by default can be either used for free indexing or for indexing with a controlled vocabulary, but with OpenKM is mandatory having a controled vocabulary.

If order having KEA running in OpenKM must be a well done configured vocabulary (Thesaurus).

KEA is a training module that uses a Thesaurus as the controller vocabulary. In order how to configure OpenKM Thesaurus take a look at Thesaurus in installation guide.

To creating KEA model must checkout openkm and thesaurus modules:

Select the svn type and type the url https://openkm.svn.sourceforge.net/svnroot/openkm/trunk/openkm to refer openkm:

Select the svn type and type the url https://openkm.svn.sourceforge.net/svnroot/openkm/trunk/thesausus to refer thesaurus:

In KEA web page could downloading file that comes with some example how to creating KEA model. In similar way using class ModelBuilder in thesaurus modules must be created the KEA model based in some vocabulary controller ( Thesaurus ).

For training KEA module is needed execute ModelBuilder class with that params:

sourceFolder 
trainingFolder 
vocabularyFile 
vocabularyType
stopwordFile 
modelFileName 
porterStemmerClass 
stopwordClass 
language 
documentEncoding

Automatic key extraction full example

You could be interested in:

• KEA [1]
• WEKA - Data mining with Open Source machine learning in Java [2]
• Aperture framework [3]
• RDF2GO [4]
• OpenRDF [5]