Difference between revisions of "Segmented Topic Model"
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Revision as of 14:50, 29 September 2012
Segmented Topic Model is a new form of topic model which can take into account the inner structures in documents. The basic ideas are:
- As in LDA, one document d has a multinomial distribution v(d) over latent topics
- In this document, each segment d,s (sentence or paragraph) also has a multinomial distribution over topics. This distribution is generated from a two-parameter Poisson-Dirichlet process r(d,s)~ Poisson-Dirichlet(v(d),a,b)
