Séminaires RALI-OLST

An Anonymizable Entity Finder in justice documents

Farzaneh Kazemi (kazemifa <at> iro (point) umontreal (point) ca)

RALI, DIRO [ATTENTION à l'heure plus matinale....]

Wednesday 11 June 2008 at 10:30 AM

Salle 3195, Pavillon André-Aisenstadt


In the Information Age, there is an increasing need to release and share textual data. However, when data contains sensitive or personal information, privacy can only be guaranteed if the sensitive data is anonymized, or de-identified, before its dissemination. Detecting personal information that should be anonymized within a text is a challenging task. We present that machine learning methods can help in detecting anonymizable entities in justice documents. Anonymizable Entity Finder system uses Maximum Entropy model as supervised machine learning approach for a binary classification.


Follow this link to subscribe to future RALI-OLST announcements.
http://rali.iro.umontreal.ca/rali/?q=fr/node/1631

See all the weekly talks for the year:

1991 1992 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024