Text Mining to Fast-Track Deserving Disability Applicants

author: John Elder, Elder Research, Inc.
published: Oct. 1, 2010,   recorded: July 2010,   views: 3509
Categories

Slides

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.
  Delicious Bibliography

Description

If your health and finances are sufficiently poor, the Social Security Administration will send you taxpayer dollars to help out. But, applying and qualifying can be a long and frustrating process - sometimes taking up to two years! In the meantime, your health and finances are undoubtedly worsening. (Likely the reason half of those appealing a rejection eventually get approved; the lack of timely help ensures their deterioration.) Yet, by mining the important text of the applications, the SSA can identify those most likely to be approved upon analyst review, and put them in a much more efficient fast track - helping all applicants. The solution involves text extraction, token collocation, Bayesian inference, and a new way to combine evidence.

See Also:

Download slides icon Download slides: kdd2010_elder_tmft_01.pdf (4.5 MB)

Download slides icon Download slides: kdd2010_elder_tmft_01.ppt (5.5 MB)


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: