Post-Doc Researcher: Golnoosh Farnadi

Date of Presentation: 
Wednesday, January 22, 2014
Quarter: 
2014 Winter
Research Focus: 

Abstract
Social networking sites are becoming an important source of users' interaction.
Their users generate lots of information about themselves and post it on these
sites, however similar to any real world data set, data are mostly incomplete,
vague, and uncertain. Understanding and modeling of social network sites (e.g.,
Facebook) in order to predict missing attribute values in proles of users would
help improving user modeling, recommendations, and personalization, among
others.

Let U = (u1, u2, ... , un) be a set of users and A = {a1, a2, ... ,am} a set of
attributes. For every user u € U and every attribute a € A we want to know
the value a(u) of attribute a of user u. We assume that potentially some but not
all of the values a(u) are known, and our goal is to predict the missing values
as accurately as possible. In this talk we explore several directions for solving
this problem.

Biography
Golnoosh Farnadi holds a M. Sc. degree in Computer Science from Delft Uni-
versity of Technology, the Netherlands (2011). Since November 2012, she is a
joint PhD student at Ghent university (UGent) and the Katholieke Universiteit
Leuven (KU Leuven) in Belgium. Currently, she is working on Personalised
AdveRtisements buIlt from web Sources (PARIS) project under supervision of
Prof. Martine De Cock and Prof. Marie-Francine Moens.