Metadata-Version: 2.0
Name: rake-nltk
Version: 1.0.0
Summary: Python implementation of the Rapid Automatic Keyword Extraction algorithm using NLTK
Home-page: https://github.com/csurfer/rake-nltk
Author: Vishwas B Sharma
Author-email: sharma.vishwas88@gmail.com
License: MIT
Keywords: nlp text-mining algorithms development
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: License :: OSI Approved :: MIT License
Classifier: Development Status :: 3 - Alpha
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Software Development :: Build Tools
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Dist: nltk

rake-nltk
=========

|Build Status| |Licence| |Coverage Status|

RAKE short for Rapid Automatic Keyword Extraction algorithm, is a domain
independent keyword extraction algorithm which tries to determine key
phrases in a body of text by analyzing the frequency of word appearance
and its co-occurance with other words in the text.

|Demo|

References
----------

This is a python implementation of the algorithm as mentioned in paper
`Automatic keyword extraction from individual documents by Stuart Rose,
Dave Engel, Nick Cramer and Wendy Cowley`_

Why I chose to implement it myself?
-----------------------------------

-  It is extremely fun to implement algorithms by reading papers. It is
   the digital equivalent of DIY kits.
-  There are some rather popular implementations out there, in python(\ `aneesha/RAKE`_) and
   node(\ `waseem18/node-rake`_) but neither seemed to use the power of `NLTK`_. By making NLTK
   an integral part of the implementation I get the flexibility and power to extend it in other
   creative ways, if I see fit later, without having to implement everything myself.
-  I plan to use it in my other pet projects to come and wanted it to be
   modular and tunable and this way I have complete control.

Versions of python this code is tested against
----------------------------------------------

-  2.7
-  3.4
-  3.5
-  3.6

Contributing
------------

Bug Reports and Feature Requests
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Please use `issue tracker`_ for reporting bugs or feature requests.

Development
~~~~~~~~~~~

Pull requests are most welcome.

.. _Automatic keyword extraction from individual documents by Stuart Rose, Dave Engel, Nick Cramer and Wendy Cowley: https://www.researchgate.net/profile/Stuart_Rose/publication/227988510_Automatic_Keyword_Extraction_from_Individual_Documents/links/55071c570cf27e990e04c8bb.pdf
.. _aneesha/RAKE: https://github.com/aneesha/RAKE
.. _waseem18/node-rake: https://github.com/waseem18/node-rake
.. _NLTK: http://www.nltk.org/
.. _issue tracker: https://github.com/csurfer/rake-nltk/issues

.. |Build Status| image:: https://travis-ci.org/csurfer/rake-nltk.svg?branch=master
   :target: https://travis-ci.org/csurfer/rake-nltk
.. |Licence| image:: https://img.shields.io/badge/license-MIT-blue.svg
   :target: https://raw.githubusercontent.com/csurfer/rake-nltk/master/LICENSE
.. |Coverage Status| image:: https://coveralls.io/repos/github/csurfer/rake-nltk/badge.svg?branch=master
   :target: https://coveralls.io/github/csurfer/rake-nltk?branch=master
.. |Demo| image:: http://i.imgur.com/wVOzU7y.gif


