lda主题模型分析文本（lda主题模型 python）



经典paper 值得一看。We describe latent Dirichlet allocation (

), a generative probabilistic model for collections of

discrete data such as text corpora.

is a three-level hierarchical Bayesian model, in which each

item of a collection is modeled as a finite mixture over an underlying set of topics. Each topic is, in

turn, modeled as an infinite mixture over an underlying set of topic probabilities. In the context of

text modeling, the topic probabilities provide an explicit representation of a document. We present

efficient approximate inference techniques based on variational methods and an EM algorithm for

empirical Bayes parameter estimation. We report results in document modeling, text classification,

and collaborative filtering, comparing to a mixture of unigrams model and the probabilistic LSI

model.

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