Fast, Flexible Models for Discovering Topic Correlation across Weakly-Related Collections

Jaan Altosaar
Jaan Altosaar
James Evans
James Evans
Richard Jean So
Richard Jean So

Conference on Empirical Methods in Natural Language Processing, pp. 1554-1564, 2015.

Cited by: 4|Views8
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Abstract:

Weak topic correlation across document collections with different numbers of topics in individual collections presents challenges for existing cross-collection topic models. This paper introduces two probabilistic topic models, Correlated LDA (C-LDA) and Correlated HDP (C-HDP). These address problems that can arise when analyzing large,...More

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