InfVocLDA

InfVocLDA is a Latent Dirichlet Allocation topic modeling package based on Variational Bayesian learning approach under online settings, developed by the Cloud Computing Research Team in [University of Maryland, College Park] (http://www.umd.edu). You may find more details about this project on our papaer [Online Latent Dirichlet Allocation with Infinite Vocabulary] (http://kzhai.github.io/paper/2013_icml.pdf) appeared in ICML 2013.

Please download the latest version from our GitHub repository.

Please send any bugs of problems to Ke Zhai (kzhai@umd.edu).

Install and Build

This package depends on many external python libraries, such as numpy, scipy and nltk. After downloading the source code packages, unzip the datasets to the 'input' directory. The package includes a few fundamental datasets --- ap, de-news and 20-newsgroup datasets.

Launch and Execute

First, redirect to the source code directory

cd InfVocLDA/src

To launch the online LDA with pre-defined vocabulary, run the following command

python -m fixvoc.launch --input_directory=../input/ --output_directory=../output/ --corpus_name=20-news --number_of_topics=10 --number_of_documents=18600 --batch_size=100

To launch the online LDA with dynamic vocabulary, run the following command

python -m infvoc.launch --input_directory=../input/ --output_directory=../output/ --corpus_name=de-news --truncation_level=4000 --number_of_topics=10 --number_of_documents=9800 --vocab_prune_interval=10 --batch_size=100 --alpha_beta=1000

Under any cirsumstances, you may also get help information and usage hints by running the following command

python -m fixvoc.launch --help
python -m infvoc.launch --help