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JACM
2010

The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies

9 years 1 months ago
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies
clustering of documents according to sharing of topics at multiple levels of abstraction. Given a corpus of documents, a posterior inference algorithm finds an approximation to a posterior distribution over trees, topics and allocations of words to levels of the tree. We demonstrate this m on collections of scientific abstracts from several journals. This model exemplifies a recent trend in statistical machine learning—the use of Bayesian nonparametric methods to infer distributions on flexible data structures. Categories and Subject Descriptors: G.3 [PROBABILITY AND STATISTICS]: Stochastic processes; I.2.7 [ARTIFICIAL INTELLIGENCE]: Text analysis General Terms: Algorithms, Experimentation Additional Key Words and Phrases: Bayesian nonparametric statistics, Unsupervised learning (To appear in the Journal of the ACM)
David M. Blei, Thomas L. Griffiths, Michael I. Jor
Added 28 Jan 2011
Updated 28 Jan 2011
Type Journal
Year 2010
Where JACM
Authors David M. Blei, Thomas L. Griffiths, Michael I. Jordan
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