John Liagouris

TL;DR: In this article, the authors proposed an anonymization technique termed disassociation that preserves the original terms but hides the fact that two or more different terms appear in the same record.

TL;DR: An anonymization technique termed disassociation is proposed that preserves the original terms but hides the fact that two or more different terms appear in the same record, which is the first to employ such a technique to provide protection against identity disclosure in the publication of sparse multidimensional data.

TL;DR: DS2, an automatic scaling controller for large-scale stream processors which combines a general performance model of streaming dataflows with lightweight instrumentation to estimate the true processing and output rates of individual dataflow operators is presented.

TL;DR: This paper proposes the first approach that prevents this type of data linkage using disassociation, an operation that transforms records by splitting them into carefully selected subsets, and can construct data that are highly useful for supporting various types of clinical case count studies and general medical analysis tasks.

TL;DR: This work presents a novel platform for the interactive visualization of very large graphs that involves an offline preprocessing phase that builds the layout of the graph by assigning coordinates to its nodes with respect to a Euclidean plane and translates user operations into simple and very efficient spatial operations in the backend.