Latent Dirichlet allocation (LDA) topic modeling in javascript for node.js. LDA is a machine learning algorithm that extracts topics and their related keywords from a collection of documents.
In LDA, a document may contain several different topics, each with their own related terms. The algorithm uses a probabilistic model for detecting the number of topics specified and extracting their related keywords. For example, a document may contain topics that could be classified as beach-related and weather-related. The beach topic may contain related words, such as sand, ocean, and water. Similarly, the weather topic may contain related words, such as sun, temperature, and clouds.
See http://en.wikipedia.org/wiki/Latent_Dirichlet_allocation
Kory Becker http://www.primaryobjects.com
Based on original javascript implementation https://github.com/awaisathar/lda.js
Added stop-words for a lot of languages https://github.com/stopwords-iso/stopwords-iso