Abstract

A large number of online databases are hidden behind form-like
interfaces which allow users to execute search queries by specifying
selection conditions in the interface. Most of these interfaces return
restricted answers (e.g., only top-k of the selected tuples), while
many of them also accompany each answer with the COUNT of the selected
tuples. We shall present techniques which leverage the COUNT
information to efficiently acquire unbiased samples of the hidden
database. We also discuss variants for interfaces which do not provide
COUNT information.

* Collaborative work with Arjun Dasgupta and Dr. Gautam Das of the
  University of Texas at Arlington

Bio

Dr. Nan Zhang is an Assistant Professor of Computer Science at the
George Washington University.  Prior to joining GWU, he was an
assistant professor of Computer Science and Engineering at the
University of Texas at Arlington from 2006 to 2008.  He received the
B.S. degree from Peking University in 2001 and the Ph.D. degree from
Texas A&M University in 2006, both in computer science.  His current
research interests span security and privacy issues in databases, data
mining, and computer networks, including privacy and anonymity in data
collection, publishing, and sharing, privacy-preserving data mining,
and wireless network security and privacy.  He received the NSF CAREER
award in 2008.