rake-nltk 1.0.0

Python implementation of the Rapid Automatic Keyword Extraction algorithm using NLTK

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.

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.