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lda-c

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Latent Dirichlet Allocation (LDA) is a tool for finding latent themes in collections of text documents. Formally called a Topic Model, this algorithm is similar to (and in some ways more robust than) earlier topic models such as Latent Semantic Analysis (Deerwester 1990) and Probabilistic LSA ... [More] (Hofmann 1999). This project is a C implementation of the variational algorithm as described in Blei et al.'s original paper, "Latent Dirichlet Allocation" (citation below). Original citation: Blei, David M.; Andrew Y. Ng, Michael I. Jordan (2003). "Latent Dirichlet Allocation". Journal of Machine Learning Research 3: 993–1022. [Less]

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  0 reviews  |  1 user  |  918 lines of code  |  0 current contributors  |  Analyzed almost 2 years ago
  lda-c latentsemanticindexing lda nlp variational topicmodel latentdirichletallocation topics
 
 
 
 

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