Supervised HDP using prior knowledge

Authors:
Boyi Xie;Rebecca J. Passonneau
Affiliations:
Center for Computational Learning Systems, Columbia University, New York;Center for Computational Learning Systems, Columbia University, New York
Venue:
NLDB'12 Proceedings of the 17th international conference on Applications of Natural Language Processing and Information Systems
Year:
2012

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Abstract

End users can find topic model results difficult to interpret and evaluate. To address user needs, we present a semi-supervised hierarchical Dirichlet process for topic modeling that incorporates user-defined prior knowledge. Applied to a large electronic dataset, the generated topics are more fine-grained, more distinct, and align better with users' assignments of topics to documents.