I’ve been doing a lot of natural-language machine-learning work both for clients and in side-projects recently. Mark Needham asked me on Twitter for some pointers to good introductory material. Here’s what I wrote for him:

Nearly all text processing starts by transforming text into vectors:
en.wikipedia.org/wiki/Vector_space_model

Often it uses transforms such as TFIDF to normalise the data and control for outliers (words that are too frequent or too rare confuse the algorithms):
en.wikipedia.org/wiki/Tf%E2%80%93idf

Collocations is a technique to detect when two or more words occur more commonly together than separately (e.g. “wishy-washy” in English) – I use this to group words into n-gram tokens because many NLP techniques consider each word as if it’s independent of all the others in a document, ignoring order:
matpalm.com/blog/2011/10/22/collocations_1/
matpalm.com/blog/2011/11/05/collocations_2/

When you’ve got a lot of text and you don’t know what the patterns in it are, you can run an “unsupervised” clustering using Latent Dirichlet allocation:
www.cs.princeton.edu/~blei/papers/Blei2012.pdf
www.youtube.com/watch?v=5mkJcxTK1sQ

Or if you know how your data is divided into topics, otherwise known as “labeled data”, then you can run “supervised” techniques such as training a classifier to predict the labels of new similar data. I can’t find a really good page on this – I picked up a lot in IM with my friend Ben who is writing a book coming out next year: blog.someben.com/2012/07/sequential-learning-book/

Here are the tools I’ve mostly been using:

• Vowpal Wabbit (classification and LDA, poor documentation, C++ high performance): https://github.com/JohnLangford/vowpal_wabbit/wiki
• Gensim (LDA, vector similarity, text processing, python): radimrehurek.com/gensim/index.html
• Mallet (classification and LDA, java): mallet.cs.umass.edu/
• Lingpipe (text analysis, clustering, classification, linguistics, java, commercial open-source): alias-i.com/lingpipe/demos/tutorial/read-me.html
• Mahout (Hadoop, classification, clustering, LDA, collaborative filtering, java): mahout.apache.org/
• Langdetect (language detection, java): code.google.com/p/language-detection/

Some blogs I like:

• matpalm.com/blog/
• blog.echen.me/
• thedatachef.blogspot.co.uk/
• www.machinedlearnings.com

MetaOptimize Q+A is the Stack Overflow of ML: metaoptimize.com/qa

The Mahout In Action book is quite good and practical: manning.com/owen/