Linnaeus provides a redis-backed Bayesian classifier. Words are stemmed, stopwords are stopped, and redis is used to allow for persistent and concurrent training and classification.

Text mining tools: named entity recognition and normalization, document classification, bag-of-words, dictionaries, etc

A simple and extensible sentiment analysis gem.

Word spell checker

A simple vector space search engine with tf*idf ranking.

A library of clustering and classification algorithms for text data.

A library for machine learning and classification

An implementation of the IMatch algorithm as described at http://www.ir.iit.edu/~abdur/Research/Duplicate.html

Pares text down to the words that matter

Use literature mining to find semantic features to describe clusers of genes

A library for machine learning and classification

A k-mean and LDA text clustering library for ruby.

A general classifier module to allow Bayesian and other types of classifications.

A simple bayesian classifier

gem install universe-parsing

Validate against blacklist of words