The primary goal of this workshop is to bring together a diverse set of researchers from multiple research areas, all of whom work on topic modeling. Statistical topic models are a class of Bayesian latent variable models, originally developed for analyzing the semantic content of large document corpora. With the increasing availability of other large, heterogeneous data collections, topic models have been adapted to model data from fields as diverse as computer vision, finance, bioinformatics, cognitive science, music, and the social sciences. While the underlying models are often extremely similar, these communities use topic models in different ways in order to achieve different goals. This one-day workshop will bring together topic modeling researchers from multiple disciplines, providing an opportunity for attendees to meet, present their work and share ideas, as well as inform the wider NIPS community about current research in topic modeling. This workshop will address the following specific goals:

* Identify and formalize open research areas – e.g., how best to evaluate topic modeling performance both within and across different application domains
* Propose, explore, and discuss new application areas
* Discuss how best to facilitate transfer of research ideas between application domains
* Direct future work and generate new application areas, novel modeling approaches, and unexplored collaborative research directions

We encourage researchers to emphasize real-world applications – ranging from specific applications to entire application domains – in their submissions, and welcome the following types of papers:

* Research papers that propose new topic models for specific applications
* Research papers that apply existing topic models to novel application domains
* Position papers and speculative papers that discuss desiderata of existing application domains or propose new domains and approaches for future topic modeling research
* Papers that discuss practical issues relating to topic models, such as parallel computation environments and scalability for massive data collections
* Papers that investigate evaluation methodologies for topic models

The workshop will consist of invited talks (5 or 6) by established researchers from multiple research communities, contributed talks (4 or 5), a poster session, and a panel session.

Invited Speakers (confirmed):

David Blei (Princeton University)
Mark Johnson (Brown University)
Eric Xing (Carnegie Mellon University)
Mark Steyvers (U.C. Irvine)
Fei-Fei Li (Stanford University)

Submission Instructions:

Submissions should be sent to:

They should include a title, authors, and abstract in plain text, and a 2-4 page extended abstract in NIPS pdf format. Final versions of extended abstracts will be posted on the workshop website.

Dates:
Submission Deadline: Friday October 23, 2009
Notifications: Monday November 9, 2009
Final Versions: Friday November 20, 2009
Workshop: December 11 or 12, 2009

Location:

Westin Resort and Spa / Hilton Whistler Resort and Spa
Whistler, B.C., Canada

http://nips.cc/Conferences/2009/

Organizers:

David Blei (Princeton University)
Jordan Boyd-Graber (Princeton University)
Jonathan Chang (Princeton University)
Katherine Heller (University of Cambridge)
Hanna Wallach (University of Massachusetts, Amherst)

Program Committee:

Edo Airoldi (Harvard University)
Hal Daumé (University of Utah)
Tom Dietterich (Oregon State University)
Laura Dietz (Max-Planck-Institut für Informatik)
Jacob Eisenstein (Carnegie Mellon University)
Tom Griffiths (University of California, Berkeley)
John Lafferty (Carnegie Mellon University)
Jia Li (Stanford University)
Andrew McCallum (University of Massachusetts, Amherst)
David Mimno (University of Massachusetts, Amherst)
Dave Newman (University of California, Irvine)
Padhraic Smyth (University of California, Irvine)
Erik Sudderth (Brown University)
Yee Whye Teh (Gatsby Unit, UCL)
Chong Wang (Princeton University)
Max Welling (University of California, Irvine)
Sinead Williamson (University of Cambridge)
Jerry Zhu (University of Wisconsin, Madison)

Contact:

nips2009@topicmodels.net