ONLINE TOPIC MODEL VISUALIZATION Allison J. B. Chaney achaney@princeton.edu (C) Copyright 2011-2014, Allison J. B. Chaney This is free software, you can redistribute it and/or modify it under the terms of the GNU General Public License. The GNU General Public License does not permit this software to be redistributed in proprietary programs. This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. ------------------------------------------------------------------------ DESCRIPTION This code uses the Django web framework [https://www.djangoproject.com], which will need to be installed. On Unix systems, this can be done with: sudo pip install Django currently requires 1.2.4 The BasicBrowser is an interface that lazily generates pages to display the results of a topic model. Since each page querys the database, the browser can keep pace with online topic models, displaying current data. It can also be used with topic models that are not online. ------------------------------------------------------------------------ INCLUDED FILES * BasicBrowser: a directory containing an online topic model browser, written in Python using the Django framework. * static: directory containing javascript, css, image files * templates: directory containing template html files with Django tags and filters * tmv_app: directory containing models and views files for the browser (see Django doc for more details) * db.py: a file to control writes to the database; this is generally the file imported into external topic model source (see wiki example) * all other .py files that come standard with Django (see Django doc for details) * onlinewikipedia.py: a modified version of the Python script that comes with Online LDA (see below for source) * Readme.txt: This file. * COPYING: A copy of the GNU public license version 3. ------------------------------------------------------------------------ WIKIPEDIA DEMO A demonstration of this browser can be run with the Wikipedia demo included with the Online LDA source: http://www.cs.princeton.edu/~blei/downloads/onlineldavb.tar If you are not familiar with the Online LDA source, it is recommended that you read its readme and explore its demo before proceeding. To run the browser with the Wikipedia demo, substitute the original [onlinewikipedia.py] file with provided replacement. For example: cp online-tmve/onlinewikipedia.py onlineldavb/onlinewikipedia.py All paths to the database need to be absolute, so modify the following lines accordingly. onlinewikipedia.py, line 27 BasicBrowser/settings.py, line 15 Finally, before running the demo, the database needs to be created. In the BasicBrowser directory, run python manage.py syncdb At this point the Online LDA demo can be run as specified in its readme, e.g. python onlinewikipedia.py 101 to run the algorithms for 101 iterations (which isn't very long). To view the browser, run the following in the BasicBrowser directory: python manage.py runserver and navigate to the following link in a web browser, reloading as desired. (The topics make take a while to be created and populated with terms.) http://127.0.0.1:8000/topic_presence Viewing a given page of the browser make take longer while the topic model is running than it does after the run completes. If you want to start over again, remove the database file, sync the database again before restarting the model. rm tmv_db; python manage.py syncdb To install the browser on a web server, see the Django documentation. ------------------------------------------------------------------------ USING THE BROWSER WITH OTHER TOPIC MODELS The browser can be used for any topic model, even if the model is not online. For algorithms written in Python, simply import the db.py file and use its functions to write to the database. For algorithms not written in Python, you need only write your data to the database, which can be done directly with sqlite3, by embeding the db.py file in your code, or by using any other method that works for you. If you have the output of a model in a file, it might be easiest to write a python script to transfer that data using db.py. It shoudl be noted that as written, db.py uses a separate thread for most writes to the database; this may not be ideal for all applications.