Theory and Applications of Topic Modeling

Dr David Newman

Department of Computer Science, University of California, Irvine

Date and time: 11.30 - 12.30, Friday 27th March, 2009

Venue: 10.08.04 (Building 10, Level 8, Room 4)

Abstract:

Topic models, a class of Bayesian statistical models for discrete data, have recently gained popularity in applications ranging from document modeling to computer vision.  Since the 2003 introduction of Latent Dirichlet Allocation (the original topic model), there have been numerous extensions to this model.  I will review the theory behind topic modelling and show some recent results of algorithmic improvements.  I will then discuss an array of application domains from improving search in digital libraries to understanding scientific disciplines using topic maps.

About the speaker:

David Newman is a Research Scientist at NICTA VRL, currently on leave from his Research Faculty position in the Department of Computer Science at the University of California, Irvine.  His research interests include machine learning, data mining and text mining. Newman received his PhD from Princeton University and was a Postdoctoral Scholar at Caltech. http://www.ics.uci.edu/~newman/

 


Seminar Organisation

Seminars are free and open to the general public. No booking is necessary. If you are interested in giving a presentation in this seminar series, or to make suggestions for speakers, please contact Xiaodong Li, the seminar co-ordinator.