Poster: Dirichlet Process Mixture Models for Verb Clustering

author: Andreas Vlachos, Computer Laboratory, University of Cambridge
published: Aug. 11, 2008,   recorded: July 2008,   views: 3773

See Also:

Download slides icon Download slides: icml08_vlachos_dpm_01.pdf (165.6 KB)

Help icon Streaming Video Help

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.


In this work we apply Dirichlet Process Mixture Models to a learning task in natural language processing (NLP): lexical-semantic verb clustering. We assess the performance on a dataset based on Levin’s (1993) verb classes using the recently introduced V-measure metric. In, we present a method to add human supervision to the model in order to to influence the solution with respect to some prior knowledge. The quantitative evaluation performed highlights the benefits of the chosen method compared to previously used clustering approaches.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: