Home

Eric Ringger edited this page Jun 5, 2015 · 9 revisions

The Topical Guide is a web application that facilitates the discovery of topical patterns and trends in large document collections. The Topical Guide relies on probabilistic topic models, such as LDA, to reveal the semantic content in such large corpora. It is an interactive tool that facilitates exploration through interaction with topics, documents, vocabulary, and metadata. Beyond interactive exploration, it allows for modification of the underlying representations, so that human insight can constrain and guide the analysis. Together, the topic models and human insight combine to reveal patterns more effectively than either could alone.

Demo

Explore the State of the Union Addresses using the Topical Guide.

Download

The code is in a git repository hosted on Github. Use the following command to clone the repository:

git clone https://github.com/BYU-NLP-Lab/topicalguide.git

Installation and Setup

See the README for installation and setup instructions.

Documentation

For more detailed information about how to use the Topical Guide, for both users and developers, see the links for documentation on the sidebar.

Papers

Our "system" paper explaining the abilities of an older version of the Topical Guide (formerly known as "The Topic Browser"):

Matthew J. Gardner, Joshua Lutes, Jeff Lund, Josh Hansen, Dan Walker, Eric Ringger, Kevin Seppi. "The Topic Browser: An Interactive Tool for Browsing Topic Models". Proceedings of the Workshop on Challenges of Data Visualization, held in conjunction with the 24th Annual Conference on Neural Information Processing Systems (NIPS 2010). December 11, 2010. Whistler, BC, Canada.

License

The code for the Topical Guide is released under the terms of the AGPLv3 or any later version of that license. If for any reason you wish to use the code under other terms, please contact the Copyright Licensing Office, Brigham Young University, 3760 HBLL, Provo, UT 84602, (801) 422-9339 or 422-3821, Email: copyright AT byu DOT edu.

We also ask that if you use this code for academic purposes, any papers that result from the use of this code should cite the Gardner et al. paper referenced above.

Contributions to the code are welcome. Currently the best way to contribute is to email a patch to the textmining AT cs DOT byu DOT edu. Because of licensing issues we ask that you assign the copyright of any patch that you contribute to BYU.

Credits

Project Leaders: Eric Ringger and Kevin Seppi

Project Members: Jordan Boyd-Graber, Schuyler Goodman, Craig Jacobson, Jeff Lund, Nozomu Okuda

Alumni: Joey Cozza, Jared Forsyth, Matt Gardner, Josh Hansen, Tobias Kin Hou Lei, Joshua Lutes, Chris Tensmeyer, Dan Walker,

Original Author: Joshua Lutes

Third-party software: See the list of third-party software used by the Topical Guide.