A Nested HDP for Hierarchical Topic Models

John Paisley, Chong Wang, David Blei, Michael I. Jordan

Jan 17, 2013 (modified: Jan 17, 2013) ICLR 2013 conference submission readers: everyone
  • Decision: conferenceOral-iclr2013-workshop
  • Abstract: We develop a nested hierarchical Dirichlet process (nHDP) for hierarchical topic modeling. The nHDP is a generalization of the nested Chinese restaurant process (nCRP) that allows each word to follow its own path to a topic node according to a document-specific distribution on a shared tree. This alleviates the rigid, single-path formulation of the nCRP, allowing a document to more easily express thematic borrowings as a random effect. We demonstrate our algorithm on 1.8 million documents from The New York Times.

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