Probabilistic models for ranking and information extraction

author: Ed Snelson, Microsoft Research, Cambridge, Microsoft Research
published: Oct. 9, 2008,   recorded: September 2008,   views: 3181


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.


I will summarize some current approaches to information extraction, which aims to obtain structured information from unstructured text sources such as the web. I will then discuss whether Bayesian modelling may be useful in this area and describe a first attempt at extracting class-attributes from web search query logs. If time remains I will move on to discuss various models for probabilistic ranking, and where possible appropriate Bayesian inference techniques.

See Also:

Download slides icon Download slides: bark08_snelson_pmfraie_01.ppt (1.1┬áMB)

Help icon Streaming Video Help

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: