Highly Multilingual News Analysis Applications

author: Ralf Steinberger, Joint Research Centre, European Commission
published: Oct. 20, 2009,   recorded: September 2009,   views: 3217

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

 Watch videos:   (click on thumbnail to launch)

Watch Part 1
Part 1 56:26
!NOW PLAYING
Watch Part 2
Part 2 29:12
!NOW PLAYING

Description

The publicly accessible Europe Media Monitor (EMM) family of applications (http://press.jrc.it/overview.html) gather and analyse an average of 80,000 to 100,000 online news articles per day in up to 43 languages. Through the extraction of meta-information in these articles, they provide an aggregated view of the news, they allow to monitor trends and to navigate the news over time and even across languages. EMM-NewsExplorer additionally collects historical information about persons and organisations from the multilingual news, generates co-occurrence and quotation-based social networks, and more. All EMM applications were entirely developed at, and are being maintained by, the European Commission’s Joint Research Centre (JRC) in Ispra, Italy.

The applications make combined use of a variety of text analysis tools, including clustering, multi-label document classification, named entity recognition, name variant matching across languages and writing systems, topic detection and tracking, event scenario template filling, and more. Due to the high number of languages covered, linguistics-poor methods were used for the development of these text mining components. See the site http://langtech.jrc.it/ for technical details and a list of publications.

The speaker will give an overview of the various applications and will then explain the workings of selected text analysis components.

See Also:

Download slides icon Download slides: ecmlpkdd09_steinberger_hmna_01.pdf (4.6 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: