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

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

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