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Hierarchical topic models and the nested Chinese restaurant process Export

In Neural Information Processing Systems(NIPS) (2003)

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2009 interest-sharing lda model nested_chinese_restaurant probability semantics tagging topic_detection topics

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We address the problem of learning topic hierarchies from data. The model selection problem in this domain is daunting -- which of the large collection of possible trees to use? We take a Bayesian approach, generating an appropriate prior via a distribution on partitions that we refer to as the nested Chinese restaurant process. This nonparametric prior allows arbitrarily large branching factors and readily accommodates growing data collections. We build a hierarchical topic model by combining...


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