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TMVE 0.1: topic model visualization engine

Depending on your objective, you may want to check out my more recent code for dynamic visualization, as this code creates static pages and is not actively maintained.


a browser of 100K Wikipedia articles

This Wikipedia browser was produced by using the results of running David Blei's LDA-C on 100,000 Wikipedia articles to find 50 topics.


to produce a browser similar to the demo above

First, download build LDA-C and run it on a dataset. For the above demo, the command looked something like:

./lda est 1/50 50 settings.txt wiki/100K/word_count.dat seeded wiki-100k-lda

Next, the LDA data will need to be processed and put into a database; for this purpose, use the database generator provided in the lib folder. Again, for the demo, the command to run the generator would be as follows.

python 100k_wiki_db wiki/100K/word_count.dat wiki-100k-lda/final.beta wiki-100k-lda/final.gamma wiki/100K/vocab.dat wiki/100K/dmap.dat

The word_count, vocab, and dmap files have the same format as LDA-c; check out it's documentation and example data.

  • vocab.dat is like vocab.txt, where the word's index matches its line number
  • word_count.dat contains the word counts for each document (see lda-c doc for format details); example ap.dat.
  • dmap.dat contains the full document content, and so would be kind of like ap.txt, but with one line per document. The idea is that people would modify the write_docs function in to match their document structure.

This DB generation can take a while for large datasets. As a short-cut, a demo 1k database is included in the demo folder, entitled 1k_demo_db.

Finally, TMVE needs to be run with a project file, which specifies what database and template to use. Templates control how the data is displayed; in this case, a basic browser is produced. The included project file wiki_project_demo.tmv is set up to run with the demo database.

The command to run TMVE with the demo project is fairly simple:

python src/ demo/wiki_project.tmv

Or, for more information as the script runs, the verbose mode is helpful:

python src/ -v demo/wiki_project.tmv

For the demo project, you will need to be connected to the Internet while TMVE generates the document pages as it must pull content from Wikipedia. When this is done, you should have a local browser (in the demo directory) like the demo above, but a little smaller.

Making Changes

adapting to other datasets and other topic model types

Creating a new template will allow you to view your data in an alternative fashion. To do so, take a look at the BasicBrowser template included in the TMVE source download.

To use another dataset, you will need to change the way documents are displayed. This is currently hard-coded into the file, in the function get_doc_display.

To try different topic models, only the database generator needs to be changed. Depending on how the output differs from LDA-C, the work to do this may be minimal.

Copyright Allison J. B. Chaney, Princeton University 2010-2015


create a browser of a corpus using a topic model; original TMVE implementation (static pages)



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