Information Extraction: Knowledge Discovery from Text
New York University –
Much of the information on the Web is encoded as text, in a form which is easy for people to use but hard for computers to manipulate. The role of information extraction is to make the structure of this information explicit, by creating data base entries capturing specified types of entities, relations, and events in the text. We consider some of the challenges of information extraction and how they have been addressed. In particular, we consider what knowledge is required and how the means for creating this knowledge has developed over the past decade, shifting from hand-coded rules to supervised learning methods and now to semi-supervised and unsupervised techniques.
Date: 2009-May-25 Time: 14:00:00 Room: 336
For more information:
INESC-ID ESR Talks – February 2023
If you are a masters/PhD student or a postdoctoral fellow, come and present your work in an informal and friendly environment – and savour some tasty snacks!
Individual talks will be 10-15 minutes plus time for feedback. Enroll on your selected date by emailing pedro.ferreira[at]inesc-id.pt.
Happening on the second Wednesday of every month (4pm-5pm):
- 15 February (Alves Redol, Room 9)
- 15 March (Alves Redol, Room 9)
- 12 April (Alves Redol, Room 9)
- 10 May (Alves Redol, Room 9)
- 14 June (Alves Redol, Room 9)
- 12 July (Alves Redol, Room 9)
We hope to see you there!