papers: Pachinko Allocation

I found a few papers about Pachinko Allocation (PA) model. Basically, this is an enhanced LDA model: in LDA model, topics are assumed to be independent, while PA introduced a tree-structure to capture the correlations and hierarchies of the topics. It sounds a reasonable assumption. This model has been extended to non-parametric version and to object recognition.


Pachinko Allocation (PA) model:

• Pachinko Allocation: DAG-Structured Mixture Models of Topic Correlations ICML 2006
• Mixtures of Hierarchical Topics with Pachinko Allocation, ICML 2007
• Pachinko Allocation: Scalable Mixture Models of Topic Correlations, JMLR 2008

Extension of PA to non-parametric model:

• Nonparametric Bayes Pachinko Allocation, UAI 2007

Applications in object recognition:

• Object Recognition Based on Dependent Pachinko Allocation Model

Code of PAM at Wei Li's webpage