From the webpage:
A graphical user interface tool for Latent Dirichlet Allocation topic modeling.
A very easy tool for exploring the use of Latent Dirichlet Allocation topic modeling.
Of course, on non-Mac machines, there is no “Double-click” on the jar file to run it, so use:
java -jar TopicModelingTool.jar
Oh, and the documentation is missing the link to the test files, see:
http://code.google.com/p/topic-modeling-tool/downloads/list
- testdatanews_music_2084docs.txt 13.3 MB
- testdata_news_economy_2073docs.txt 13.0 MB
- testdata_news_fuel_845docs.txt 5.3 MB
- testdata_braininjury_10000docs.txt 9.6 MB
I used testdata_news_music_2048docs.txt file, set to 100 topics with the default options and the learning process took 52 seconds and the complete process 66.056 seconds. Your mileage will vary but fast enough for smallish data sets.
At least in a session, you can’t change the output directory.
I could see using this in a class to explore a body of material for creation of topic maps.