LDA4j

LDA4j

A Java implemention of LDA(Latent Dirichlet Allocation). Inference topics from a set of documents with few lines of Java code.

How To Use

• code

public static void main(String[] args)
{
    // 1. Load corpus from disk
    Corpus corpus = Corpus.load("data/mini");
    // 2. Create a LDA sampler
    LdaGibbsSampler ldaGibbsSampler = new LdaGibbsSampler(corpus.getDocument(), corpus.getVocabularySize());
    // 3. Train it
    ldaGibbsSampler.gibbs(10);
    // 4. The phi matrix is a LDA model, you can use LdaUtil to explain it.
    double[][] phi = ldaGibbsSampler.getPhi();
    Map[] topicMap = LdaUtil.translate(phi, corpus.getVocabulary(), 10);
    LdaUtil.explain(topicMap);
}

• output

…

• corpus The data/mini is some documents included in this project, which use space to segment words. Feel free to replace it with yours.
• algorithm Mainly depend on Gregor Heinrich's great work. Read more about this implementation on《LDA入门与Java实现》