wink-jaro-distance

An Implementation of Jaro Distance Algorithm by Matthew A. Jaro

$3

De-duplicate short strings such as names by computing similarity and distance between a pair of strings using wink-jaro-distance. It is an implementation of Jaro Distance Algorithm that determines the similarity/distance by taking into account the insertions, deletions and transpositions.

$3

Use npm to install:

npm install wink-jaro-distance --save

$3

``javascript
// Load Jaro Distance Function
var jaro = require( 'wink-jaro-distance' );

console.log( jaro( 'father', 'farther') );
// -> { distance: 0.04761904761904756, similarity: 0.9523809523809524 }

console.log( jaro( 'Angelina', 'Angelica') );
// -> { distance: 0.08333333333333337, similarity: 0.9166666666666666 }

console.log( jaro( 'Flikr', 'Flicker' ) );
// -> { distance: 0.09523809523809523, similarity: 0.9047619047619048 }

console.log( jaro( 'abcdef', 'fedcba' ) );
// -> { distance: 0.6111111111111112, similarity: 0.38888888888888884 }
`

Try experimenting with this example on Runkit in the browser.

$3

##### Table of Contents

- jaro
- Parameters
- Examples

#### jaro

Computes Jaro distance and similarity between strings s1 and s2.

Original Reference: UNIMATCH:
A Record Linkage System: Users Manual pp 104.

##### Parameters

- s1 string — the first string.
- s2 string — the second string.

##### Examples

`javascript
jaro( 'daniel', 'danielle' );
// -> { distance: 0.08333333333333337, similarity: 0.9166666666666666 }
jaro( 'god', 'father' );
// -> { distance: 1, similarity: 0 }
`

Returns object containing distance and similarity values between 0 and 1.

$3

Computes Jaro distance and similarity between strings s1 and s2.

Original Reference: UNIMATCH:
A Record Linkage System: Users Manual pp 104.

Parameters

- s1 string — the first string.
- s2 string — the second string.

Examples

`javascript
jaro( 'daniel', 'danielle' );
// -> { distance: 0.08333333333333337, similarity: 0.9166666666666666 }
jaro( 'god', 'father' );
// -> { distance: 1, similarity: 0 }
`

Returns object containing distance and similarity` values between 0 and 1.

$3

If you spot a bug and the same has not yet been reported, raise a new issue or consider fixing it and sending a pull request.

$3

Wink is a family of open source packages for Statistical Analysis, Natural Language Processing and Machine Learning in NodeJS. The code is thoroughly documented for easy human comprehension and has a test coverage of ~100% for reliability to build production grade solutions.

$3

wink-jaro-distance is copyright 2017-18 GRAYPE Systems Private Limited.

It is licensed under the terms of the MIT License.