Rake

[sunagparasu]

• Collaborator: Parasu Nagesh Sunag

Rake: Rapid Automatic Keyword Extraction

• Rapid Automatic Keyword Extraction (RAKE) is a Domain-Independent keyword extraction algorithm in Natural Language Processing.

Installation and Use

• RAKE can be downloaded from the terminal using pip install rake-nltk

• To use RAKE, The python code needs to be imported into the environment. This can be achieved by import rake and import operator

• After the code has been imported, enter the path of your results file and apply the algorithm on the text.

filepath = "keyword_extraction.txt" rake_object = rake.Rake(filepath) text = "Feature extraction is not that complex. There are many algorithms available that can help you with feature extraction. Rapid Automatic Keyword Extraction is one of those" sample_file = open(“data/docs/fao_test/w2167e.txt”, ‘r’) text = sample_file.read() keywords = rake_object.run(text) print “Keywords:”, keywords

• A simpler method would be to use the keyword extraction section of the google colaboratory to obtain the keywords.
• Change the chapter paths to your requirement and enter the method as rake and run the cell to obtain the result.

Features

• The concept of RAKE is built on three matrices Word Degree, Word Frequency, and ratio of the degree to frequency.

Evaluation

• A good feature of RAKE would be the use of matrices and ratios while a disadvantage would be the lack of an argument to customize the extraction of n_grams.

Result

• The following .csv file was obtained by running the keywords extraction section of the google colab.
  Rake_keywords.csv