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A semi-unsupervised language independent morphological analyzer useful for stemming unknown language text, or getting a rough estimate of possible parses for morphemes in a word. Input: a corpus. Uses compression, maximum entropy and fieldlinguistics.

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iLanguage

A semi-unsupervised language independent morphological analyzer useful for stemming unknown language text, or getting a rough estimate of possible parses for morphemes in a word. Uses compression, maximum entropy and fieldlinguistics.

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Release History

  • v1.0 April 16 2009 - Initial implementation in bash and perl
  • v2.0 Jul 3 2010 - Implementation in C++
  • v3.0 April 30 2011 - Implementation in Groovy
  • v4.0 July 20 2012 - Implementation in JavaScript Map Reduce
  • v4.1 Nov 29 2013 - Added more high level functions for gloss lookup
  • v5.0 Jan 9 2014 - Implementation in CommonJS

License

This project is released under the Apache 2.0 license, which is an very non-restrictive open source license which basically says you can adapt the code to any use you see fit.

How to Contribute Code

  • Signup for a GitHub account (GitHub is free for OpenSource)
  • Click on the "Fork" button to create your own copy.
  • Leave us a note in our issue tracker to tell us a bit about the bug/feature you want to work on.
  • You can follow the 4 GitHub Help Tutorials to install and use Git on your computer.
  • Feel free to ask us questions in our issue tracker, we're friendly and welcome Open Source newbies.
  • Edit the code on your computer, commit it referencing the issue #xx you created ($ git commit -m "fixes #xx i changed blah blah...") and push to your origin ($ git push origin master).
  • Click on the "Pull Request" button, and leave us a note about what you changed. We will look at your changes and help you bring them into the project!
  • Feel the glow of contributing to OpenSource :)

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A semi-unsupervised language independent morphological analyzer useful for stemming unknown language text, or getting a rough estimate of possible parses for morphemes in a word. Input: a corpus. Uses compression, maximum entropy and fieldlinguistics.

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  • JavaScript 74.1%
  • TeX 13.6%
  • CSS 3.8%
  • C++ 2.6%
  • Java 2.1%
  • Shell 1.0%
  • Other 2.8%