Fast, Flexible Models for Discovering Topic Correlation across Weakly-Related Collections
Conference on Empirical Methods in Natural Language Processing, pp. 1554-1564, 2015.
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
PPT (Upload PPT)