rake-js
TL;DR
Quick Start? Follow the installation and sample usage. Don't forget to read the details before deploying to production.
Installation
npm install @shopping24/rake-js
Sample Usage
const deDict = require('@shopping24/rake-js/dist/de');
const rakejs = require('@shopping24/rake-js');
const text = 'Die Kopf-Rumpf-Länge des Jaguars beträgt 112 cm bis 185 cm, hinzu kommt ein 45–75 cm langer Schwanz. ' +
'Die Schulterhöhe liegt im Durchschnitt bei etwa 70 cm. Obwohl insgesamt kräftiger und massiger gebaut als der ' +
'Leopard, ist sein Schwanz deutlich kürzer als der des afrikanisch-asiatischen Verwandten. Das Körpergewicht variiert ' +
'stark zwischen unterschiedlichen Regionen und schwankt zwischen 36 und 158 kg. Weibchen sind dabei etwa 10–20 % ' +
'kleiner und entsprechend leichter als männliche Tiere. Darüber hinaus besteht eine ausgeprägte geographische ' +
'Variation. So sind Jaguare in Nord- und Mittelamerika deutlich kleiner als Jaguare in Südamerika. Männliche Tiere in ' +
'Belize haben im Schnitt etwa ein Gewicht von 60 kg, während Jaguarmännchen in Venezuela und Brasilien um die 90–100 ' +
'kg wiegen. Weibliche Jaguare in Brasilien wiegen durchschnittlich fast 80 kg.[2]';
const { result } = rakejs.extract(text)
.setOptions({ articles: deDict.articles, stopWords: deDict.stopwords.concat(deDict.articles) })
.pipe(rakejs.extractKeyPhrases)
.pipe(rakejs.extractAdjoinedKeyPhrases)
.pipe(rakejs.keywordLengthFilter)
.pipe(rakejs.distinct)
.pipe(rakejs.scoreWordFrequency)
.pipe(rakejs.sortByScore);
console.log(result);
Background story
What is RAKE?
RAKE is the acronym for Rapid Automated Keyword Extraction. The basic algorithm is described by Stuart Rose, Dave Engel,
Nick Cramer and Wendy Cowley in their paper "Automatic keyword extraction from individual documents"
(©2010, John Wiley & Sons, Ltd, Source click here).
In short RAKE describes splitting a text into fragments by stop words. Stop words are always considered to be irrelevant
to the context. The RAKEd result of Red Zebra and Jaguar
would therefore be [Red Zebra, Jaguar]
.
The score is then calculated by counting the individual words and and creating degrees based on the length of found
fragments.
What is this repository about?
This repository includes advanced methods in addition to the original RAKE description. Furthermore we added a
functional wrapper as feature for a more flexible way of handling keyword extraction. The process consists of these
steps:
- Extracting fragments from any given text using various available methods.
- Score the fragments.
- Retrieve the end result.
Extraction and scoring functions from any source making use of the Phrases and Phrase classes may be used and executed
in the desired order.
For reference you can find included extraction and scoring functions under src/utils/
.
Included helper functions are accessible in src/lib/
.
Pipeline Reference
The extract method and phrases class provide a convenient way to apply multiple filtering and scoring methods on a
given text.
Phrases
Class
A Phrases object is created and returned by the extract(text)
function.
Methods
Method | Arguments | Returns | Description |
---|
pipe | method : Callable Function | <Phrases> | method Receives and must return Phrases object. result must be an array of Phrase objects. |
toPhrase | phrase : String,
score : Number (optional) | <Phrase> | Helper function, creates and returns new Phrase object from given phrase and score . Pushing into result property of Phrase object needs to be done manually. |
setOptions | options : Object | <Phrases> | Provided key/value pairs get merged with stored Phrases options and made available to pipeline methods. See documentation of Extraction and Scoring Functions for available options. |
Properties
Property | Type | Mutable | Description |
---|
result | <Phrase[]> | Y | Contains result array of the previous pipe function. Pipe functions must not change object properties but reassign the full object with either an empty array or an array of Phrase objects. |
original | <string> | N | The input provided with the extract(text) function. |
options | <object> | N | Key/value pairs of options provided when using setOptions . |
Phrase
Class
A Phrase
object represents a single extracted fragment with the calculated score. The score value may be changed as
needed during pipeline processing.
Properties
Property | Type | Mutable | Description |
---|
phrase | <Phrase> | Y | The extracted text fragment. |
score | <string> | Y | The calculated score of the text fragment. |
Method | Access/Change | Description | Options |
---|
extractKeyPhrases | Accesses original , Pushes records into result | Basic RAKE implementation, splitting original by words from stopWords array. | stopWords<Array> |
extractAdjoinedKeyPhrases | Accesses original , Pushes records into result | Extracts combined with stop words combined fragments (ie. Birds and Bees) from original and pushes result into results . | stopWords<Array> ,
minKeyWordsPerPhrase<Number> At least this number of keywords must exist within the phrase excluding stop words,
maxKeyWordsPerPhrase<Number> At maximum this number of keywords must exist within the phrase excluding stop words |
Included Scoring Functions
Method | Access/Change | Description | Options |
---|
scoreWordFrequency | Accesses original , Changes score in result.<Phrase>[] | Adds to the score of each phrase the word counts. | stopWords<Array> |
Included Convenience Functions
Method | Access/Change | Description | Options |
---|
distinct | Accesses and changes result | Removes duplicate values from result | - |
keywordLengthFilter | Accesses and changes result | Removes individual words from each phrase not matching the minWordLength and maxWordLength length and removes whole phrases from result not matching the minKeyWordsPerPhrase and maxKeyWordsPerPhrase options. | minWordLength<Number , maxWordLength<Number> , minKeyWordsPerPhrase<Number> , maxKeyWordsPerPhrase<Number> |
sortByScore | Accesses and changes result | Sort result array by score descending. | - |
Included Helpers and Library Functions
Method | Where | Arguments | Returns | Description |
---|
extract | @shopping24/rake-js | text<String> | <Phrases> | Helper function, constructs Phrases object. |
options | @shopping24/rake-js/src/lib/options | overrides<Object> : Override default options | <Object> | Get options object with key/value pairs. Includes get(key<String>, default = defaultValue<*>) method returning value for key in object. If key does not exist defaultValue is returned. |
splitByStopWords | @shopping24/rake-js/src/lib/splitByStopWords | sentence<String> ,
stopWords<String[]> | <String[]> | Split sentence by stopWords into fragments. |
splitSentences | @shopping24/rake-js/src/lib/splitSentences | text<String> | <String[]> | Split text by line- and paragraph separator and dash, open, close, initial and final punctuation into fragments. |
splitWords | @shopping24/rake-js/src/lib/splitWords | text<String> | <String[]> | Split text into individual words by non-letter, mark and number characters. |
Included Dictionary
We included a basic german stop words and articles lists under dictionary/de.js
and dist/de.js
. For best results
concat both lists for the stopWords
option. articles
may be used individually for other extraction and scoring
functions.
Writing your own Extraction and Scoring Methods
It's recommended to look into the already defined extraction and scoring functions. These rules must be followed:
- Pipeline functions receive
Phrases
as first argument and must return same, - the
result
property of the Phrases
object must be an empty array or an array of Phrase
objects, - you may change
result
by reassigning/overriding the value, do not change individual properties.
You know, if there is one thing that I have learned, it is that we must obey the rules of the game. We can pick the game, Niko Bellic. But we cannot change the rules.