* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project
Download management sciences - Tippie College of Business
Document related concepts
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.