Text corpus calculation in Javascript.


Text corpus calculation in Javascript. Supports Chinese, English. See demo.

This library is a spin-off project from HTML5 Word Cloud.

Load wordfreq.js script to the web page, and run:

// Create an options object for initialization
var options = {
  workerUrl: 'path/to/wordfreq.worker.js' };
// Initialize and run process() function
var wordfreq = WordFreq(options).process(text, function (list) {
  // console.log the list returned in this callback.

WordFreq() methods are chainable, for example,

// Process 3 strings and get corpus of all the texts.
  .getList(function (list) {

To use this library synchronously, load wordfreq.worker.js and use the WordFreqSync interface. Check API.md for available options and methods.

Command-line interface is available, powered by Node.js. To install globally, run

npm install -g wordfreq

Example usage:

wordfreq ~/mypost.txt | less
cat ~/mypost.txt | wordfreq - | less

Corpus is calculated with a simple N-gram algorithm and sub-string filter. Here is an article in Traditional Chinese on how HTML5 Word Cloud is being done.

Porter Stemming Algorithm is included for processing English.

To run tests, first you would need to pull the required QUnit library by running

git submodule init
git submodule update

Then, start a localhost HTTP server, for example,

python -m SimpleHTTPServer 8009

Point your browser to http://localhost:8009/test/ to start testing.

You may also run the tests with PhantomJS by running

phantomjs test/qunit/addons/phantomjs/runner.js http://localhost:8009/test/

You will find all the information you need to write testcases on the QUnit website. All non-trivial code submission are expected to accompany with testcases.

Known Gecko issue: The testcases will make Firefox choke; Web Worker will stop working after a few reloads. This was since fixed in bug 785248 on Oct. 3, 2012, so use Firefox 18 (currently Aurora) instead for testing.

PhantomJS on Travis-CI exhibits random hang, results random falling test result; but here is the badge: