Experiments with Non-parametric Topic Models
In topic modelling, various alternative priors have been developed, for instance asymmetric and symmetric priors for the document-topic and topic-word matrices respectively, the hierarchical Dirichlet process prior for the document-topic matrix and the hierarchical Pitman-Yor process prior for the topic-word matrix. For information retrieval, language models exhibiting word burstiness are important. Indeed, this burstiness effect has been show to help topic models as well, and this requires...[Show more]
|Collections||ANU Research Publications|
|Source:||Experiments with Non-parametric Topic Models|
|01_Buntine_Experiments_with_2014.pdf||604.73 kB||Adobe PDF||Request a copy|
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.