Topic Models
نویسنده
چکیده
Here, K is the number of components in the mixture model. For each k, f(x; θk) is the pdf of component number k. The scalar αk is the proportion of component number k. The specific topic model we consider is called latent Dirichlet allocation (LDA). (The same abbreviation is also used for linear discriminant analysis, which is unrelated.) LDA is based on the intuition that each document contains words from multiple topics; the proportion of each topic in each document is different, but the topics themselves are the same for all documents.
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A probabilistic topic model assumes that documents are generated through a process involving topics and then tries to reverse this process, given the documents and extract topics. A topic is usually assumed to be a distribution over words. LDA is one of the first and most popular topic models introduced so far. In the document generation process assumed by LDA, each document is a distribution o...
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