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A Correlated Topic Model implementation in Python.

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PyCTM

PyCTM is a Correlated Topic Modeling package, please download the latest version from our GitHub repository.

Please send any bugs of problems to Ke Zhai ([email protected]).

Install and Build

This package depends on many external python libraries, such as numpy and scipy. Download and install the package with

git clone https://github.com/kzhai/PyCTM.git
cd PyCTM
python setup.py install

This will install the library pyctm on your system.

Launch and Execute

Assume the PyCTM package is downloaded under directory $PROJECT_SPACE/src/, i.e.,

$PROJECT_SPACE/src/PyCTM

To prepare the example dataset,

tar zxvf pnas-abstract.tar.gz

To launch PyCTM, first redirect to the directory of PyCTM source code,

cd $PROJECT_SPACE/src/PyCTM

and run the following command on example dataset,

python bin/launch_train.py --input_directory=./pnas-abstract --output_directory=./ --number_of_topics=10 --training_iterations=50

The generic argument to run PyCTM is

python bin/launch_train.py --input_directory=$INPUT_DIRECTORY/$CORPUS_NAME --output_directory=$OUTPUT_DIRECTORY --number_of_topics=$NUMBER_OF_TOPICS --training_iterations=$NUMBER_OF_ITERATIONS

You should be able to find the output at directory $OUTPUT_DIRECTORY/$CORPUS_NAME.

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

python bin/launch_train.py --help

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