Package Exports

kmeans-categorize-text
kmeans-categorize-text/index.js

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (kmeans-categorize-text) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

Node.js text clustering - kmeans-categorize-text-js

What is k-means clustering?

K-means clustering is an unsupervised machine learning algorithm used to find groups in a dataset. The objective of k-means clustering is to divide a dataset into groups (clusters) of similar items.

To improve the result, the words are compared using the Jaro–Winkler string distance algorithm that will return a number between 0 and 1 which tells how closely the strings match (0 = not at all, 1 = exact match) e.g:

var natural = require('natural');
console.log(natural.JaroWinklerDistance("dixon","dicksonx")); // 0.7466666666666666
console.log(natural.JaroWinklerDistance('not', 'same'));      // 0 (No match)

Installation

$ npm install kmeans-categorize-text

Usage

To use k-means clustering you need to provide a dataset with objects with id and text:

const kMeansText = require('kmeans-categorize-text');

const dataSet = [
    {id: 1, text: "Leaves sway in the gentle breeze, crafting a soothing harmony of nature's tune" },
    {id: 2, text: "Waves collide against the shore, bearing whispers of secrets from the depths below" },
    {id: 3, text: "The sun dips below the tranquil horizon, adorning the sky with shades of orange and pink" },
    {id: 4, text: "Snowflakes pirouette in the wintry air, covering the earth in a gentle, white embrace" },
    {id: 5, text: "Urban lights shimmer like stars in the evening, brightening the lively streets below" },
    {id: 6, text: "Trees whisper in the soft breeze, weaving a tranquil melody through the forest" },
    {id: 7, text: "Waves break upon the coastline, echoing the ancient rhythms of the sea" },
    {id: 8, text: "The horizon blushes as the sun dips, casting a golden glow across the landscape" },
    {id: 9, text: "Frost kisses the ground, painting a delicate pattern of ice across the earth" },
    {id: 10,text: "Streetlights flicker like fireflies, guiding the way through the bustling cityscape" },
];
const groups = 3;
const excludeWords = ['dips']
kMeansText(dataSet, groups, [], result => console.log(result), error => console.log(error));

Output

The method returns an object with the category group as the key and the array objects as values.

{
    whispers: {
        '2': 'Waves collide against the shore, bearing whispers of secrets from the depths below',
            '3': 'The sun dips below the tranquil horizon, adorning the sky with shades of orange and pink',
            '7': 'Waves break upon the coastline, echoing the ancient rhythms of the sea',
            '9': 'Frost kisses the ground, painting a delicate pattern of ice across the earth'
    },
    landscape: {
        '8': 'The horizon blushes as the sun dips, casting a golden glow across the landscape'
    },
    crafting: {
        '1': "Leaves sway in the gentle breeze, crafting a soothing harmony of nature's tune",
            '4': 'Snowflakes pirouette in the wintry air, covering the earth in a gentle, white embrace',
            '5': 'Urban lights shimmer like stars in the evening, brightening the lively streets below',
            '6': 'Trees whisper in the soft breeze, weaving a tranquil melody through the forest',
            '10': 'Streetlights flicker like fireflies, guiding the way through the bustling cityscape'
    }
}

Params

Name	Type	Default
data	array of objects {id, text}	[ ]
groups	integer	2
excludeWords	array of strings	[ ]
onClusterize	callback to success (result)	console.log
onError	callback to error (error)	console.log

Reference

Implementing K-Means Clustering From Scratch in JavaScript

Natural string distance