Boosting is a general method for improving the accuracy of learning algorithms. We use boosting to construct improved privacy-preserving synopses of an input database. These are da...
Malicious users can exploit the correlation among data to infer sensitive information from a series of seemingly innocuous data accesses. Thus, we develop an inference violation d...
Integration of heterogeneous data types is a challenging problem, especially in biology, where the number of databases and data types increase rapidly. Amongst the problems that o...
We propose an extension to current view-based mediator systems called model-based mediation, in which views are defined and executed at the level of conceptual models (CMs) rather...
XML schema design has two opposing goals: elimination of update anomalies requires that the schema be as normalized as possible; yet higher query performance and simpler query exp...
Nuwee Wiwatwattana, H. V. Jagadish, Laks V. S. Lak...