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Reduction :: Topic Models
In Python
- (many)
In statsR
- (many)
- topic modeling in R
- LDAvis and gh-pages
- Introduction to Text Analysis and Topic Modeling with R
In Javascript
Latent semantic analysis (LSA) is a technique in natural language processing, in particular in vectorial semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms. Wikipedia
In natural language processing, Latent Dirichlet allocation (LDA) is a generative model that allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar. Wikipedia
Topic modeling is a form of text mining, a way of identifying patterns in a corpus. You take your corpus and run it through a tool which groups words across the corpus into 'topics' journalofdigitalhumanities
Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. Wikipedia
Topics word clouds and associated blog post
LDA-Based Topic Modelling in Javascript, update
LDA-Based Topic Modelling in Javascript