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Transcript
MANAGEMENT SCIENCES SEMINAR SERIES
Predictive Analytics in a Personalized Online World: Complex
Networks and Privacy
Elena Zheleva
Ph.D. in Computer Science from the University of Maryland College
Park, 2011
December 16, 2015
2:30-3:20 pm
S401 Pappajohn Business Building
Abstract
The abundance of personal data that people share online provides an opportunity to develop a new
category of information technology products, ones that are powered by data and sophisticated user
models. Data science products range from personalized recommendations to fostering healthy online
communities. At the core of data science is machine learning, and my research goal is to improve
predictive modeling paradigms which balance machine learning model accuracy with privacy guarantees
for users whose data drives these models. I am particularly interested in complex network data where the
attributes of the data records exhibit statistical dependencies that do not satisfy the traditional machine
learning assumptions of independence and identical distributions, an area known as statistical relational
learning.
In this talk, I will go over some of the big data problems and challenges faced by e-commerce businesses
by giving examples from my research at LivingSocial. I will cover emerging topics, such as geospatial
recommendations and incentivized sharing. I will also present my work on machine learning algorithms
that can use information from people's social environments, in order to infer their personal traits.I build
algorithms of increasing complexity, from linear classifiers to higher-order Markov Random Fields,
which allow us to incorporate the social network structure into a collective inference framework. I will
discuss the privacy implications of such algorithms for social media users and businesses in the light of a
specific Facebook case study.
Biography
Elena Zheleva earned her Ph.D. in Computer Science from the University of Maryland College Park in
2011. Her research interestslie at the intersection of machine learning, data mining and computational
social science, including the related problems of maintaining anonymity and privacy online. She has
presented her research at top-tier conferences, such as KDD and WWW. She has 17 peer-reviewed
publications with over 1,000 citations, and is the co-author of the book "Privacy in Social Networks." In
the last four years, Elena built and led the Data Science team at LivingSocial.More information about
Elena’s research and publications is available at http://www.umiacs.umd.edu/~elena.