Hi all,
Just a reminder that this fully remote event is happening on Wednesday!
On Thu, Mar 12, 2020 at 12:29 PM Janna Layton <jlayton(a)wikimedia.org> wrote:
Hi all,
The next Research Showcase will be live-streamed on Wednesday, March 18,
at 9:30 AM PDT/16:30 UTC. We’ll have a presentation on topic modeling by
Jordan Boyd-Graber. A question-and-answer session will follow.
YouTube stream:
https://www.youtube.com/watch?v=fiD9QTHNVVM
As usual, you can join the conversation on IRC at #wikimedia-research. You
can also watch our past research showcases here:
https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase
This month's presentation:
Big Data Analysis with Topic Models: Evaluation, Interaction, and
Multilingual Extensions
By: Jordan Boyd-Graber, University of Maryland
A common information need is to understand large, unstructured datasets:
millions of e-mails during e-discovery, a decade worth of science
correspondence, or a day's tweets. In the last decade, topic models have
become a common tool for navigating such datasets even across languages.
This talk investigates the foundational research that allows successful
tools for these data exploration tasks: how to know when you have an
effective model of the dataset; how to correct bad models; how to measure
topic model effectiveness; and how to detect framing and spin using these
techniques. After introducing topic models, I argue why traditional
measures of topic model quality---borrowed from machine learning---are
inconsistent with how topic models are actually used. In response, I
describe interactive topic modeling, a technique that enables users to
impart their insights and preferences to models in a principled,
interactive way. I will then address measuring topic model effectiveness in
real-world tasks.
Overview of topic models:
https://mimno.infosci.cornell.edu/papers/2017_fntir_tm_applications.pdf
Topic model evaluation:
http://umiacs.umd.edu/~jbg//docs/nips2009-rtl.pdf
Interactive topic modeling:
http://umiacs.umd.edu/~jbg//docs/2014_mlj_itm.pdf
Topic Models for Categorization:
http://users.umiacs.umd.edu/~jbg//docs/2016_acl_doclabel.pdf
--
Janna Layton (she, her)
Administrative Assistant - Product & Technology
Wikimedia Foundation <https://wikimediafoundation.org/>
--
Janna Layton (she, her)
Administrative Assistant - Product & Technology
Wikimedia Foundation <https://wikimediafoundation.org/>