Mixtures of Hierarchical Topics with Pachinko Allo cation
published: June 23, 2007, recorded: June 2007, views: 577
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
The four-level pachinko al location model (PAM) (Li & McCallum, 2006) represents correlations among topics using a DAG structure. It does not, however, represent a nested hierarchy of topics, with some topical word distributions representing the vocabulary that is shared among several more specific topics. This paper presents hierarchical PAM -- an enhancement that explicitly represents a topic hierarchy. This model can be seen as combining the advantages of hLD's topical hierarchy representation with PAM's ability to mix multiple leaves of the topic hierarchy. Experimental results show improvements in likelihood of held-out documents, as well as mutual information between automatically-discovered topics and humangenerated categories such as journals.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !